RESEARCH CENTRE

Inria Centre
at the University of Bordeaux

2023
ACTIVITY REPORT

IN PARTNERSHIP WITH:

Institut Polytechnique de Bordeaux

Project-Team

AUCTUS

Robots for Humans at work

DOMAIN

Perception, Cognition and Interaction

THEME

Robotics and Smart environments

Contents

Project-Team AUCTUS

1 Team members, visitors, external collaborators

2 Overall objectives

3 Research program

3.1 Analysis and modeling of human behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.1 Scientific Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2 Operator / robot coupling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.1 Human-Robot interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.2 Cobot adaptive assistance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 Design of cobotic systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3.1 Architectural design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3.2 Control design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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4 Application domains

10
4.1 Factory 4.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

5 Social and environmental responsibility

6 Highlights of the year

10

11

7 New software, platforms, open data

11
7.1 New software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
7.1.1 pycapacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
7.1.2 PandaCapacityAR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
7.1.3 RobotReachSBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
7.1.4 Qontrol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
7.1.5 HYPO_MPC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
7.1.6 lmpcpp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
7.1.7 Active Constraint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
7.1.8 ROS Haptic Teleop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
7.1.9 Chai3D Haptic Driver
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
7.1.10 Bioctus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
7.2 New platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
7.2.1 Ball catcher
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
7.2.2 ATROCE : Attention Tunneling and RObotic Collaboration Experiments . . . . . . . . 15
7.2.3 MAXIFORCE: Maximal isometric force capacities measurement platform . . . . . . . 15
7.2.4 Trajectory Modulation Platform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
7.2.5 Gimbal Platform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
7.2.6 Physical ability visualisation platform based on Augmented Reality tools . . . . . . . 16

8 New results

16
8.1 Human Factors and cognitive approaches in human/system interactions . . . . . . . . . . . 16
8.1.1 Attention Sharing Handling Through Projection Capability Within Human-Robot

Collaboration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
8.1.2 Adaptive task sharing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
8.1.3 Human perception of object properties . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
8.2 Human Behavior Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
8.2.1 Holistic view of Inverse Optimal Control by introducing projections on singularity

curves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
8.2.2 Improvement of the robustness of the projected inverse optimal control problem . . 18
8.2.3 Study of Motor Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

8.2.4 Observing and recording information on an expert task . . . . . . . . . . . . . . . . . 18
8.2.5 Searching for best-fitting musculoskeletal models approximating an individual’s

upper limb force capacities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
8.3 Human Robot Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
8.3.1 A coupled view of the physical abilities of human-robot dyad for the online quantit-

ative evaluation of assistance needs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

8.3.2 Prediction of pose errors implied by external forces applied on robots: towards a

metric for the control of collaborative robots . . . . . . . . . . . . . . . . . . . . . . . . 21

8.3.3 Re-expression of manual expertise through semi-automatic control of a teleoperated

8.4 Robotics and control

system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
8.3.4 Haptic guidance to assist human motion . . . . . . . . . . . . . . . . . . . . . . . . . . 22
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
8.4.1 Predictive Control of Collaborative Robots in Dynamic Contexts . . . . . . . . . . . . 23
8.4.2 Model Predictive Control for shared human-robot tasks . . . . . . . . . . . . . . . . . 23
8.4.3 Criteria for evaluation of serial and parallel robot leg . . . . . . . . . . . . . . . . . . . 23
8.4.4 Optimization of a novel parallel leg architecture . . . . . . . . . . . . . . . . . . . . . . 24
8.4.5 Elasto-Geometric Calibration of a TALOS Humanoid Robot . . . . . . . . . . . . . . . 24
8.4.6 Solving semi-constrained end-effector path planning problems . . . . . . . . . . . . 24
8.4.7 Real time jogging respecting robot and task constraints . . . . . . . . . . . . . . . . . 24

9 Bilateral contracts and grants with industry

25
9.1 Airbus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
9.2 Stellantis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
9.3 Solvay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
9.4 Farm3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
9.5 Aerospline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
9.6 Fuzzy Logic Robotics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

10 Partnerships and cooperations

27
10.1 International initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
10.2 International research visitors
10.2.1 Visits of international scientists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
10.2.2 Visits to international teams
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
10.3.1 Other european programs/initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
10.4 National initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
10.5 Regional initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

10.3 European initiatives

11 Dissemination

35
11.1 Promoting scientific activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
11.1.1 Scientific events: organisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
11.1.2 Scientific events: selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
11.1.3 Journal
11.1.4 Invited talks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
11.1.5 Leadership within the scientific community . . . . . . . . . . . . . . . . . . . . . . . . 37
11.1.6 Scientific expertise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
11.1.7 Research administration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
11.2 Teaching - Supervision - Juries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
11.2.1 Teaching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
11.2.2 School
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
11.2.3 Supervision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
11.2.4 Juries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
11.3 Popularization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
11.3.1 Articles and contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
11.3.2 Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

11.3.3 Event . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
11.3.4 Interventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

12 Scientific production

43
12.1 Major publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
12.2 Publications of the year
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
12.3 Cited publications

Project AUCTUS

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Project-Team AUCTUS

Creation of the Project-Team: 2020 April 01

Keywords

Computer sciences and digital sciences

A5.1.1. – Engineering of interactive systems

A5.1.2. – Evaluation of interactive systems

A5.1.3. – Haptic interfaces

A5.1.5. – Body-based interfaces

A5.1.7. – Multimodal interfaces

A5.1.9. – User and perceptual studies

A5.4.2. – Activity recognition

A5.4.4. – 3D and spatio-temporal reconstruction

A5.4.5. – Object tracking and motion analysis

A5.4.8. – Motion capture

A5.5.1. – Geometrical modeling

A5.6.2. – Augmented reality

A5.10.1. – Design

A5.10.2. – Perception

A5.10.3. – Planning

A5.10.4. – Robot control

A5.10.5. – Robot interaction (with the environment, humans, other robots)

A5.10.8. – Cognitive robotics and systems

A6.2.5. – Numerical Linear Algebra

A6.2.6. – Optimization

A6.4.6. – Optimal control

A6.5.1. – Solid mechanics

A8.3. – Geometry, Topology

A9.5. – Robotics

A9.8. – Reasoning

Other research topics and application domains

B1.1.11. – Plant Biology

B1.2.2. – Cognitive science

B2.8. – Sports, performance, motor skills

B5.1. – Factory of the future

B5.2. – Design and manufacturing

B5.6. – Robotic systems

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Inria Annual Report 2023

B9.5.5. – Mechanics

B9.6. – Humanities

B9.9. – Ethics

Project AUCTUS

3

1 Team members, visitors, external collaborators

Research Scientists

• David Daney [Team leader, INRIA, Senior Researcher, HDR]

• Vincent Padois [INRIA, Senior Researcher, HDR]

• Margot Vulliez [INRIA, Researcher]

Faculty Member

• Jean-Marc Salotti [BORDEAUX INP, Professor, HDR]

Post-Doctoral Fellow

• Vincent Fortineau [INRIA, until Sep 2023]

PhD Students

• Virgile Batto [CNRS, LAAS, Toulouse]

• Alexis Boulay [FARM3 , CIFRE]

• Raphael Bousigues [Inria, until Nov 2023, Larsen, Nancy]

• Benjamin Camblor [INRIA]

• Ahmed-Manaf Dahmani [INRIA, from Dec 2023, in Intership, from April to Sept 2023]

• Louis Garcia [INRIA, until Aug 2023, CeRCA, Poitiers ]

• Elio Jabbour [INRIA]

• Pierre Laguillaumie [Université de Poitiers, teaching fellow, until Sep 2023, PPRIME]

• Gautier Laisne [INRIA]

• Erwann Landais [INRIA]

• Antun Skuric [INRIA, until Nov 2023]

• Nicolas Torres Alberto [PSA, CIFRE, until Oct 2023]

Technical Staff

• Guillaume De Mathelin De Papigny [INRIA, Engineer, until Aug 2023]

• Sebastien Dignoire [INRIA, Engineer]

• Lucas Joseph [INRIA, Engineer, SED, Bordeaux]

• Loic Mazou [INRIA, Engineer, from Nov 2023]

Interns and Apprentices

• Romain Dantu [INRIA, Intern, from Feb 2023 until Jul 2023]

• Pierre Garnault [INRIA, Intern, from Feb 2023 until Aug 2023]

• Claire Houziel [INRIA, Intern, from May 2023 until Jun 2023]

• Axel Plantey–Veux [INRIA, Intern, from Apr 2023 until May 2023]

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Inria Annual Report 2023

Administrative Assistant

• Nathalie Robin [INRIA]

External Collaborators

• Nasser Rezzoug [University of Poitiers, HDR]

• Jean-Christophe Sarrazin [ONERA, HDR]

2 Overall objectives

The project of the Auctus team is to design the collaborative robotics cells of the future.

The robotics community still tends to separate the cognitive (HRI) and physical (pHRI) aspects of
human-robot interaction. One of the main challenges is to characterize the task as well as biomechanical,
physiological and cognitive capabilities of humans in the form of physical constraints or objectives
for the design of cobotized workstations. This design must be understood in a large sense: the choice
of the robots’ architecture (cobot, exoskeleton, human-robot interface, etc.), the dimensional design
(human/robot workspace, trajectory calculation, etc.), the coupling mode (comanipulation, teleoperation,
etc.) and the control strategy. The approach then requires the contributions of the human and social
sciences to be considered in the same way as those of exact sciences. The topics considered are broad,
ranging from cognitive sciences, ergonomics, human factors, biomechanics and robotics.

The first challenge is to evaluate the hardship at work, the well-being of the operators and, further
upstream, their cognitive state which impacts their sensorimotor strategy while performing a task. In the
industry, the ergonomic analysis of the task is carried out by an ergonomist based on direct but often ad
hoc observations. However, the context is changing: the digitization of factories, through the installation
of on-site sensors, allows longitudinal observation of machines and humans. The available information
can thus allow us to rethink the way in which the evaluation of activities is carried out. Currently, an
emerging subdomain, named ergonomic robotics, adapts available ergonomic criteria (RULA, REBA, etc.)
to the evaluation of robotic cells. However, such criteria are related to the (quasi-static) posture of the
operator, which limits the understanding of human motor strategies over a long period of time. Similarly,
kinematic or biomechanical analyses may tend to see humans as a high-performance machine to be
optimized. This can make sense for a top-level athlete, but repeating actions in the industry over a day,
months or years of work means that a temporary change of posture, possibly poorly rated according to
usual ergonomic criteria, can actually be a good long-term strategy. These questions directly link motor
and cognitive aspects that can be reflected in particular strategies such as the fatigue or the expertise
(manual and cognitive). This approach has not been widely explored in robotics while it could determine
the right criteria to adapt the behavior of a cobot.

The second challenge is to define a methodology to link the analysis of the task and the induced
human movements to the robot design. Several of our industrial projects have shown that there is a
significant conceptual distance between the ergonomist, expert in task analysis and psychology, and the
robotician, expert in mechanics, control and computer science, which makes it very difficult to analyze
the needs and define the specifications of the technical solution. To fill these methodological gaps, it is
necessary to better define the notion of tasks in the context of a human/robot coupling, on the basis of
case studies. We also have to establish a typology of human/robot interaction by taking into account the
different physical and cognitive constraints, in a very detailed fashion, and their potential psychological,
organizational or ethical impacts.

The third challenge addresses the need to think about the control laws of collaborative robots in terms
of human/robot coupling. The effectiveness of this coupling requires an ability to predict future human
actions. This prediction should make the interaction more intuitive but also aims at optimizing the robot
assistive behavior from the point of view of "slow" phenomena, such as fatigue. The major challenge is,
therefore, to move from reactive to predictive control laws, by integrating a human prediction model, both
in terms of movement strategies and decision strategies. Beyond the great computational complexity of
predictive approaches, obtaining prediction models is an ambitious challenge. It is indeed necessary to

Project AUCTUS

5

learn models that are quite complex, due to the physical realities they can account for, and quite simple
from a computational point of view.

3 Research program

3.1 Analysis and modeling of human behavior

3.1.1 Scientific Context

The purpose of this axis is to provide metrics to assess human behavior. Our human study specifically
focuses on industrial operators. We assume the following working hypotheses: the operator’s task and
environmental conditions are known and circumscribed; the operator is trained in the task, production
tools and safety instructions; the task is repeated with more or less frequent intervals. We aim at analyzing:

• the physical and cognitive fragility of operators in order to meet assistance needs;

• cognitive biases and physical constraints leading to a loss of the operator safety;

• ergonomics, performance and acceptance of the production tool.

In the industrial context, these questions are tackled through the fields of work ergonomics and
cognitive sciences. Four main axes are typically addressed: physiological/biomechanical, cognitive,
psychological and sociological studies. We particularly focus on the biomechanical, cognitive and
psychological aspects, as described by the ANACT [30, 32]. The aim is to translate these factors into
metrics, optimality criteria or constraints which can be implemented in our methodologies to better
analyze, design and control the collaborative robots.

A review of ergonomic workstation evaluation helps in positioning our desired contributions in
robotics. Ergonomists evaluate the gesture through the observation of the workstations and, generally,
through questionnaires. This requires long periods of field observation, followed by analyses based on
ergonomic grids (e.g. RULA [44], REBA [36], LUBA [40], OWAS [39], ROSA [59],...). Until then, the use of
more complex measurement systems was reserved for laboratories, particularly in biomechanical studies.
The development of inexpensive sensors, such as IMUs (Inertial Measurement Units) or RGB-D cameras,
makes it possible to consider a digitalized, and therefore objective, observation of the gesture, posture
and more generally of human movement and at the same time collecting information on physiological
states. Thanks to these sensors, which are more or less intrusive, observation systems can be permanently
installed on production lines. This change of paradigm opens the door to longitudinal observations. It
can be compared to the evolution of maintenance, which became predictive.

Ergonomic robotics has recently taken an interest in this new evaluation paradigm to adapt the robot
behavior in order to reduce ergonomic risks. This ergonomic adaptation complements the conventional
approaches that only consider the performance of the action produced by the human in interaction with
the robot. However, ergonomic criteria are usually based on the principle that the comfort positions are
distant from the human joint limits. The notation are compatible with an observation of the human oper-
ator through the eye of the ergonomist. In practice, such evaluations are inaccurate and subjective [62].
Moreover, they only consider quasi-static human positions, without taking into account the evolution of
the person’s physical, physiological and psychological state. We aim at extending this approach to more
reliable and comprehensive ergonomic metrics. The repetition of gestures, the solicitation of muscles
and joints, are questions that must complete these analyses. A method used by ergonomists to limit
biomechanical exposures is to increase variations in motor stress by rotating tasks [60]. However, this
type of extrinsic method is not always suitable in the industrial context [43] where we place our research
efforts.

Through these human analyses, the Auctus team aims at revising the use of collaborative robots in
the workplace to vary the operator’s environment and encourage more appropriate motor strategies.
This approach relies on biomechanical studies of the intrinsic variability of the motor system allowed
by the joint redundancy of the human body. This motor variability refers to the alternation of postures,
movements and muscle activity observed in the individual to perform a requested task [60]. This variation

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Inria Annual Report 2023

leads to differences between the motor coordination used by each operator, and conveys the notion of
motor strategy [37].

The cognitive dimension of ergonomics must also be addressed in our approach to reduce the mental
workload and foster wellness of the worker. We believe that known sensorimotor strategies can be a phys-
ically quantifiable reflection of the operator’s cognitive state. For example, human motion measurements
can be used to predict fatigue [55] and, therefore, adjust the robot physical assistance. A key challenge
here is to better analyze human manual expertise (dexterous and cognitive) to adapt the human-robot
interaction. The expertise embodies the operators’ decision-making process while perceiving, under-
standing, and anticipating their gestures to preserve their safety, comfort, and performance in the task.
We particularly aim at adapting and refining known human cognitive models (multisensory perception
[34], situation awareness [33]) to infer the influence of the task context and environment on the operator
behavior.

3.1.2 Methodology

How can we observe, understand and quantify human sensorimotor and cognitive strategies to better
design and control the behavior of the cobotic assistant?

When we study systems of equations (kinematic, static, dynamic, musculoskeletal, etc.) to model

human behavior, several problems appear and explain our methodological choices:

• the large dimension of the problems to be considered, due to the human body complexity (eg. joint,

muscle and placement redundancy);

• the variability of the parameters, for example, physiological (set of operators), geometric (set of
possible trajectories, postures, and placements of the operator), and static parameters (set of forces
that the operator must produce with respect to the task and context);

• the uncertainties in the measurement and the model approximations.

The idea is to start from a description of redundant workspaces (geometric, static, dynamic...). We
use set-theory approaches, based on interval analysis [61], [49], which meet the variability requirement
and cope with model and measurement uncertainties. Another advantage of such techniques is that
they allow the results to be certified, which is essential to address safety issues. Some members of the
team have already achieved success in mechanical design for performance certification and robot design
[46]. By extending these set-theory approaches to our problem, a mapping of ergonomic, efficient, and
safe movements can be obtained, in which we project the operators’ motor strategies. Biomechanical,
ergonomic, and cognitive metrics can, then, be defined and evaluated to quantify the human behavior in
specific work situations.

It is therefore necessary to:

• model human capabilities, both at the musculoskeletal and the perceptive/cognitive levels, to allow
for global, yet detailed, analyses as well as efficient integration of such knowledge in the control of
the collaborative robots.

• propose new ergonomic, biomechanical, robotic, and cognitive indices which will link different
types of performances while taking into account the influence of fatigue, stress, level of expertise,
etc.;

• divide the task and the gesture into homogeneous phases: this process is complex and depends on
the type of studied index and the techniques being used. We are exploring several methods: inverse
optimal control, learning methods, techniques from signal processing;

• develop interval extensions of the proposed indices. The indices are not necessarily the result of
a direct model, and algorithms must be developed or adapted to compute them (calculation of
manipulability, Uncontrolled Manifold, etc.);

• Aggregate proposals into a dedicated interval-analysis library for human behavior studies (use of

and contribution to the existing ALIAS-Inria and the open source IBEX library).

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The major contribution of the methodology is to embrace in the same model the measurement uncer-
tainties (important for on-site use of measurement equipment), the variability of tasks and trajectories
(proper to dexterous industrial operations), and the physiological characteristics of the operators (critical
adaptability to every individual). The originality of the approach is to combine biomechanical, ergonomic
and cognitive metrics with the usual performance indices to build a comprehensive and objective analysis
of human behavior.

Other avenues of research are being explored, particularly around the inverse optimal control [50],
to project human movements on the basis of the performance or ergonomic indices. Such a projection
would offer new interpretations and enhance the analysis of human behaviors.

3.2 Operator / robot coupling

This research axis is at the frontier between humans and robots and focuses on optimal methods to
couple together these two entities to perform joint activities. This raises questions which are directly
related both to human models and abilities (axis 1) and robot control (axis 3). Two main concerns must
be addressed to form an effective human-robot dyad.

3.2.1 Human-Robot interaction

The first step to couple the operator and cobot together at work is to provide interaction modalities
through which the agents can communicate and coordinate. The interaction can be direct, where
the robot and operator act together in the same shared environment, or the operator can remotely
perform the task with the robot through a teleoperation system (which reflects the remote interaction
and potentially corrects for punctual weaknesses). The level and type of human-robot interactions are
chosen with respect to the task, the context, or other human factors. The challenge is, then, to predict the
joint human-robot behavior and capabilities for each interaction situation and collaborative context.

The formal computation of joint human-robot capabilities can be given thanks to the models and
evaluation indices built in the Axis 1. We can focus on quantifying how the interaction with the robot will
impact the human sensorimotor strategy (changes in the posture, positions, forces, etc., induced by the
robot) and recomputing metrics such as human fatigue and motor variability[54] and the Mover project.
We can further use the biomechanical and robotic models to consider a unified operator-robot entity and
to compute their joint abilities (e.g. common human-robot force capabilities [58]).

Developing human cognitive and sensorimotor models to account for the effect of the human-robot
interaction could provide a valuable tool to evaluate cobotic systems and collaborative works. However,
the accuracy of these models must be addressed. We wish to understand how the robot influences
the operator’s work and thus how his mental model of the task evolves according to the interactions
with the robot. The challenge is, then, to predict a behavior of the operator that takes into account
his cognition in the interaction situations. Preliminary literature results have shown that key cognitive
mechanisms in human teaming may transfer to human-robot collaboration, such as joint human-robot
action representation [31] or coordination mechanisms [48]. But the situation awareness of the operator
is modified by the interaction with the robot [53]. Developing a joint mental model which accurately
capture the human-robot interaction can later guide the design of relevant interaction modalities to
improve the team understanding [2].

3.2.2 Cobot adaptive assistance

Taking into account the coupling between the operator and the robot at the control level is also central to
the team’s objectives. We wish to demonstrate how a collaborative robot can be used to mediate between
a control objective which optimizes task performances, safety and comfort (what we consider as the
expertise trinity), on one hand, and the action model of the human interacting with the robot (the inferred
human intent), on the other hand. Such an arbitration in the control law adapts the robot assistive
behavior to better collaborate with the operator. This shared-autonomy concept is the focus of part of our
research. It can range from a discrete task allocation between the agents to an effectively shared task [47].
We are strongly confident that the notion of expertise is central to adjust the cobot behavior. The
robot controller is designed to increase the level of expertise in the operator/robot team: it optimizes the

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human-centered metrics (safety criteria, biomechanical and cognitive comfort, etc.) and provides a gain
in performances (joint human-robot capabilities). But it also aims at preserving the operator particular
expertise and know-how in the center of the activity. Manual expertise of highly skilled operators needs
to be analyzed respectively on its dynamic aspects and on the ability to synchronize with other operators
in the environment. Better understanding expertise is envisioned as a way to alleviate the operators of
repetitive and easy operations while maintaining their ability to perform expert gestures based on the
complexity of the task.

Furthermore, this research axis raises the question of the modification of the work induced by
collaborative robots for expert operators. While the overall goal is to make use of robots to punctually
or continuously improve the work conditions of these operators (and clearly not to replace them), the
presence of these robots necessarily impacts the work referential and thus the expertise itself. One of
the central questions, yet to be tackled, relates to the original and core part of the expertise that should
remain unchanged. The proposed modeling of the operator/robot coupling and interaction is a first
avenue to predict possible changes in the expertise. It can be input to the controller to constraint the
robot to naturally let the operator take the expert decisions.

3.3 Design of cobotic systems

3.3.1 Architectural design

Is it necessary to cobotize, robotize or assist the human being? Which mechanical architecture meets the
task challenges (a serial cobot, a specific mechanism, an exoskeleton)? What type of interaction (H/R
cohabitation, comanipulation, teleoperation)? These questions are the first requests from our industrial
partners. For the moment, we have few comprehensive methodological answers to these requests.
Choosing a collaborative robot architecture is a difficult problem [41]. It becomes even more complex
when the architectural design is approached from concurrent cognitive ergonomic, biomechanical and
robotic perspectives. There are major methodological and conceptual differences in these areas. It is,
therefore, necessary to bridge these representational gaps and to propose a global and generic approach
that takes into consideration the expectations of the robotician to model and formalize the general
properties of a cobotic system as well as those of the ergonomist to define the expectations in terms of an
assistance tool.

To do this, we propose a user-centered design approach, with a particular focus on human-system
interactions. From a methodological point of view, this requires to develop a structured experimental
approach. It aims at characterizing the task to be carried out ("system" analysis) but also at capturing
the physical markers of its realization (required movements and efforts, ergonomic stress, etc). This
specification must be done through the prism of a systematic study of the exchanged information (type
and modality) needed by the humans to perform the considered task. On the basis of these analyses, the
main challenge is to define a decision support tool for the choice of the robotic architecture and for the
specifications of the role assigned to the robot and the operator as well as their interactions.

The evolution of the chosen methodology is for the moment empirical, based on the user cases

regularly treated in the team (see sections on contracts and partnerships).

The process can be summarized through the following steps:

• identify expert or difficult jobs on industrial sites. This is done through visits and exchanges with

our partners (manager, production manager, ergonomist...);

• select some challenging use cases to be studied and, then, observe the operator in its ecological
environment. Our tools allow us to produce a force-motion analysis, based on previously defined
ergonomic criteria, and a physical evaluation of the task in terms of expected performances, from
experiments and simulations. In parallel, an evaluation of the operator expertise and cognitive
strategy is done by means of questionnaires;

• synthesize these observatory results into design requirements to deduce: the robotic architectures
to be initiated, the key points of human-robot interaction to be developed, and the difficulties in
terms of human factors to be taken into account.

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The different human and task analyses take advantage of the expertise available within the auctus
team. The team has already worked on the current dominant approach: the use of human models to
design the cobotic cell through virtual tools [3]. We would like to gradually introduce the additional evalu-
ation criteria presented above. However, the very large dimensions of the treated problems (modeling of
the body’s dofs and the constraints applied to it) makes it difficult to carry out a certified analysis. We
choose to go through the calculation of the human workspace and performances, which is not yet done
in this field. The idea here is to apply set theory approaches, using interval analysis as already discussed
in section 3.1.2. The goal is, then, to extend the human constraints to intervals, which integrate the
model variability, and to play them in virtual reality during simulations of the tasks. This would allow the
operator to check his trajectories and scenarios not only for a single case study but for sets of cases. For
example, it can be verified that, regardless of the bounded sets of simulated operator physiologies, the
physical constraints of a simulated trajectory are not violated. Therefore, the assisted design tools certify
cases of use as a whole. Moreover, the intersection between the human and robot workspaces/capabilities
provides the necessary constraints to certify the feasibility of a task in the interaction situation. Overall,
this integration of human and task-related physical constraints in the design process brings to better
cobotic systems. In the future, we will similarly develop tools to include human cognitive markers into
the design approach.

This research line merges the contributions of the other axes, from the analysis of the human behavior
and capabilities in its environment for an identified task, the prediction of the effects of the interac-
tion/coupling strategy with the robot, to the choice of a mechanical architecture from the resulting design
constraints. The proposed task-oriented and human-centered methodology is perfectly integrated into
an Appropriate Design approach. It can be used for the dimensional design and optimization of robots,
again based on interval analysis. The challenges are the change of scale in models that symbiotically
consider the human-robot pair, the uncertain, flexible and uncontrollable nature of human behavior,
and the many evaluation indices needed to describe them.

It is worth noting that we aim at developing a global mechatronic design approach, which would build
upon the design constraints to specify the robot hardware and controller at once. The chosen set-theory
computational methodology is particularly appropriate to meet this objective since the interval-based
representation of the design constraints can be directly and equally used to set the control constraints.

3.3.2 Control design

The control laws of collaborative robots from the major robot manufacturers differ little or not at all from
the existing control laws in the field of conventional industrial robotics. Security is managed a posteriori,
as an exception, by a security PLC / PC. It is therefore not an intrinsic property of the controller. This
strongly restricts possible physical interactions 1 and leads to sub-optimal operation of the robotic system.
It is difficult in this context to envision tangible human-robot collaboration. Collaborative operation
requires, in this case, a control calculation that integrates safety and ergonomics as a priori constraints.
The control of truly collaborative robots in an industrial context is, from our point of view, under-
pinned by two main issues. The first one is related to the macroscopic adaptation of the robot’s behaviour
according to the phases of the production process. The second one is related to the fine adaptation of the
degree and/or nature of the robot’s assistance according to the ergonomic state of the operator. If this
second problem is part of a historical dynamics in robotics that consists in placing safety constraints,
particularly those related to the presence of a human being, at the heart of the control problem [35] [45,
38], it is not approached from the more subtle point of view of ergonomics where the objective cannot be
translated only in terms of human life or death, but rather in terms of long-term respect for their physical
and mental integrity. Thus, the simple and progressive adoption by a human operator of the collaborative
robot intended to assist him in his gesture requires a self-adaptation in the time of the command. This
self-adaptation is a fairly new subject in the literature [51, 52].

At the macroscopic level, the task plan to be performed for a given industrial operation can be
represented by a finite state machine. To avoid increasing the human’s cognitive load by explicitly asking
him to manage transitions for the robot, we propose to develop a decision algorithm which would ensure
discrete transitions from one task (and the associated assistance mode) to another based on an online

1In the ISO TS 15066 technical specification on collaborative robotics, human-robot physical interaction is allowed but perceived

as a situation to be avoided.

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estimate of the current state of the human-robot couple. The associated scientific challenge is to establish
a link between the robot’s involvement and a given working situation. We propose an incremental
approach to learn this complex relationship. Its first stage will consist in identifying the general and
relevant control variables to conduct this learning in an efficient and reusable way, regardless of the
particular calculation method of the control action. Then, physically-realistic simulations and real-world
experiments will be used to feed this learning process.

To handle mode transitions, we propose to explore the richness of the multi-tasking control formalism
under constraints [42]. It would ensure a continuous transition from one control mode to another
while guaranteeing compliance with a certain number of robot control constraints. Some of these
constraints convey the ergonomic specifications and are dependent on the state of the robot and of the
human operator, which, by nature, is difficult to predict accurately. We propose, again, to exploit the
interval-analysis paradigm to efficiently formulate ergonomic constraints robust to the various existing
uncertainties.

Purely discrete or reactive adaptation of the control law would make no sense given the slow dynamics
of certain physiological phenomena such as fatigue. Thus, we propose to formulate the control problem
as a predictive problem where the impact of the control decision at a time t is anticipated at different
time horizons. This requires a prediction of human movement and knowledge of the motor variability
strategies it employs. This prediction is possible on the basis of the supervision at all times of the
operational objectives (task in progress) in the short term. However, it requires the use of a virtual human
model and possibly a dynamic simulation to quantify the impact of these potential movements in terms of
performances, including ergonomics. It is impractical to use a predictive command with simulation in the
loop with an advanced virtual manikin model. We therefore suggest to adapt the prediction horizon and
the complexity of the corresponding model in order to guarantee a reasonable computational complexity.

4 Application domains

4.1 Factory 4.0

The 4th industrial revolution (factory 4.0) is characterized by the integration of digital technologies
into the production process, in order to meet the challenge of customizing services and products. This
agility requires making manufacturing and maintenance lines flexible and versatile. This adaptation
capacity is a characteristic of the human being, which puts him at the center of the production apparatus.
However, this can no longer be done at the expense of the human operators’ health and well-being. How
can we reconcile the enhancement of our manual and analytical expertise, the ever desired increase in
productivity and manufacturing quality, while reducing the hardship at work? Collaborative robotics,
which we are seeking to build, is one of the key solutions to meet these societal challenges. By assisting
humans while performing dangerous and painful tasks, the collaborative robot complements and helps
them in their phases of physical and cognitive fragility.

More generally, we are interested in workstation cobotization, in the manufacturing and assembly
industries but also in the construction and craft industries. The application areas are related to regional
needs in aeronautics, maintenance, water and waste treatment. In most of these cases, it is possible to
define the tasks and to evaluate the stakes and added value of our work.

5 Social and environmental responsibility

The scientific positioning of Auctus has an explicit social objective: assisting industrial workers to
improve their working conditions through the appropriate limitations of physical solicitations and the
improvement of their cognitive comfort. This has a direct societal impact on the health of the population
and regarding the preservation of industrial skills and expertise in the local and national industrial
ecosystem.

From an environmental point of view, the research goals of Auctus do not explicitly aim at improving
the human footprint on the planet or at better understanding environmental related issues and processes.
Yet, some of our projects can have a direct impact on these issues. This impact is for example directly
related to the application context in the case of our collaboration in the domain of remote operation of

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technical skills with the Farm3 company. Indeed, this company aims at producing plants locally, with a
reduced physical footprint while minimizing water consumption. We also envision a less direct but more
fundamental impact of our work in the control, mechatronics and mechanical architecture domains
where we aim at exploiting at best robot capabilities. In the long term, the impact of this work should
lead to a reduction of the size of robots and of the amount of energy they consume to achieve a given task.
This is clearly in line with the general objective of saving energy as well as the natural resources.

6 Highlights of the year

This year, we would like to highlight several activities that support and enrich our research, while broad-
ening our fundamental perspectives in our research areas. Firstly, we played an active part in bringing
new advances in robotics to a wider public by participating in the events associated with the Robocup
held in Bordeaux in July 2023. Our involvement extended to the organization of scientific events such
as JNRH’23 and RosConfr’23. In addition, we showcased our scientific results of recent years through
demonstrations specially designed for the general public, presented at the RoboCup.

This year also demonstrated our ability to carry out numerous experiments with human subjects,
not only to collect the data essential for obtaining our results, but also to illustrate the interest of our
contributions in cognitive science, human/robot interaction and biomechanics.

In addition, as part of the Robsys program at the University of Bordeaux, we took part in an in-depth
study of our scientific partiques, particularly in robotics, from an ethical point of view. Led by Sylvie
Michel from the Institut de recherche en gestion des organisations at the Université de Bordeaux, the
study prompted us to question our ethical practices and achievements in the field of robotics. It has also
prompted forward-looking reflections within the team on the implementation of robot ethics right from
the design stage.

7 New software, platforms, open data

7.1 New software

7.1.1 pycapacity

Name: An efficient task-space capacity calculation package for robotics and biomechanics

Keywords: Computational geometry, Kinematics, Robotics, Biomechanics

Scientific Description: Python package pycapacity provides a set of tools for evaluating task space
physical ability metrics for humans and robots, based on polytopes and ellipsoids. The aim of
pycapacity is to provide a set of efficient tools for their evaluation in an easy to use framework
that can be easily integrated with standard robotics and biomechanics libraries. The package
implements several state of the art algorithms for polytope evaluation that bring many of the
polytope metrics to the few milliseconds evaluation time, making it possible to use them in online
and interactive applications.

The package can be easily interfaced with standard libraries for robotic manipulator rigid body
simulation such as robotic-toolbox or pinocchio, as well as human musculoskeletal model bio-
mechanics softwares opensim and biorbd. The package can also be used with the Robot Operating
System (ROS).

The package additionally implements a set of visualization tools for polytopes and ellipsoids
based on the Python package matplotlib intended for fast prototyping and quick and interactive
visualization.

Functional Description: Pycapacity is a python package which provides a framework for the generic task-
space capability calculation of robotic serial manipulators and human musculoskeletal models,
based on the ellipsoid and polytope metrics. Additionally, the package also provides a set of
generic polytope evaluation algorithms for standard polytope formulations, that can be used as a
standalone library.

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URL: https://github.com/auctus-team/pycapacity

Publications: hal-04316801, hal-03369576, hal-02993408

Authors: Antun Skuric, Vincent Padois, David Daney, Nasser Rezzoug

Contact: Antun Skuric

7.1.2 PandaCapacityAR

Keywords: Unity 3D, Augmented reality, Robot Operating System (ROS), Polytopal meshes, Robotics

Functional Description: Unity HoloLens project for visualizing Panda robot’s physical ability polytopes
in Augmented Reality (AR). Complements the pycapacity package and interfaces with ROS architec-
tures using the Unity Robotics Hub.

URL: https://gitlab.inria.fr/auctus-team/people/antunskuric/demos/polytope_ar_dem

o/pandacapacityar

Contact: Antun Skuric

7.1.3 RobotReachSBA

Name: Sampling based robot reacable space approximation

Keywords: Robotics, Computational geometry, Triangulation

Functional Description: This package implements an efficient method for sampling-based reachable
space approximation for robotic manipulators, given a certain horizon time of interest. The
proposed method accounts for the robot’s non-linear kinematics and allows the non-convex
characterisation of the robot’s reachable spaces.

URL: https://gitlab.inria.fr/auctus-team/people/antunskuric/example/reachable_wor

kspace

Contact: Antun Skuric

7.1.4 Qontrol

Name: Quadratic Optimization coNTROL

Keywords: Robotics, Control, Optimisation

Functional Description: Qontrol is a tool for the generic formulation of robotic control problems in the
form of constrained optimization problems. It is initially intended for fixed-base polyarticulated
robots. It allows to easily create tasks and constraints in the control law.

Author: Lucas Joseph

Contact: Lucas Joseph

7.1.5 HYPO_MPC

Name: Hyper Paramter optimization for Model-Predictive Control-HYPOMPC

Keywords: Robotics, Telerobotics, Control, Optimal control, Shared control

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Functional Description: The GitLab code, developed for the HYPO-MPC project, serves to enhance the
performance of a given Model Predictive Controller based on user requirements. It is common
to observe diverse behaviors generated by the controller, which are highly sensitive to coefficient
parameters. These parameters often require extensive tuning, and adjusting one may inherently
impact others.

The proposed code aims to streamline the tuning process, which is often quasi-impossible to
achieve optimally manually. It provides users with options to select optimal parameters that can
results in better accuracy, convergence speed, overshooting or computation time.

The code can be utilized by roboticists that are not expert or doesn’t have the time to go through
the tuning process of their controller.

URL: https://gitlab.inria.fr/auctus-team/people/eliojabbour/hyper-paramter-opti

mization-for-model-predictive-control-hypompc

Contact: Elio Jabbour

7.1.6 lmpcpp

Keyword: Collaborative robotics

Functional Description: Linear Model Predictive Controller used for research in robotics motion plan-

ning for safety, regarding this project: https://auctus-team.gitlabpages.inria.fr/publications/2022/icra23_mpc/

URL: https://auctus-team.gitlabpages.inria.fr/publications/2022/icra23_mpc/

Contact: Nicolas Torres Alberto

7.1.7 Active Constraint

Keywords: Haptic guidance, Haptic, Telerobotics

Scientific Description: The implementation of an active constraint or virtual guide in a teleoperation
context with a haptic interface aims to encourage operators to follow a desired behaviour while
allowing a certain freedom of action. This package also includes the integration of a generic formula
enabling a continuous transition between the different types of generic guides (potential fields,
spring-damper and guide tube).

Functional Description: active_constraint defines the following parameters: stiffness and damping
factors for 3 different types of guidance (potential field, spring-damper and guide tube), as well as
threshold distances and parameters enabling guidance to be generated using a generic approach.
The integration of a RVIZ plugin means that it is possible to change on the fly between each guide
and to modify the above-mentioned parameters. The package subscribes to the position and
velocity topics of the robot and the scaled haptic interface in the robot workspace. These positions
and speeds are used to generate a guidance force which is sent to the communication hub linked
to the haptic interface. This package also allows the definition of obstacles and targets required to
generate guidance, the relative poses are then published.

Contact: Alexis Boulay

Participants: Alexis Boulay, Margot Vulliez, David Daney

7.1.8 ROS Haptic Teleop

Keywords: Telerobotics, Haptic

Functional Description: ros_haptic_teleop defines the following parameters : scaling factor and trans-
formation matrix between two robot and haptic frames, homing poses for both robots, and control
gains used for homing of the robots or to maintain the haptic device pose. An integrated RViz plugin

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handles the different modes of operation (teleop, homing, maintain) from buttons of the visual
interface. The package subscribes to the pose and velocity topics of the robot and the haptic device.
It transforms these references (scaling and rotation) in the other robot’s space, and publishes the
transformed quantities (scale_pose and scale_velocity). These transformed pose/velocity are input
to the robot motion controller (external). It also subscribes to the external force sensed by the robot
and publishes the transformed value to generate a direct haptic feedback on the interface (external
force controller). It interfaces with external haptic controllers, by subscribing to their command
topics, such as the guiding force (active constraint) or the shared pose and velocity (blending), and
by integrating them to the robots’ control inputs. These external references are enabled through
activation parameters (enable_ac and enable_blending).

Contact: Alexis Boulay

Participants: Alexis Boulay, Margot Vulliez

7.1.9 Chai3D Haptic Driver

Keywords: Telerobotics, Haptic

Functional Description: This driver is based on the chai3d library. It handles any haptic device which
has been defined in chai3d/src/devices. Falcon device of Novint and Omega/Sigma/Delta devices of
Force Dimension are available by default. Device specifications such as the maximal force, stiffness,
and damping, are made accessible as ros messages. This driver provides cyclical exchanges with
the opened haptic device. It publishes pose and velocity data on ros topics. It subscribes to the
desired force topic to provide the haptic feedback through the interface. It also manages the device’s
gripper/buttons through dedicated ros topics.

Contact: Margot Vulliez

Participants: Margot Vulliez, Alexis Boulay

7.1.10 Bioctus

Keywords: Biomechanics, Symbolic computation

Functional Description: Python module to create a kinematic chain actuated by cables and/or muscles.
It allows the system jacobian computation as well as the cable wire matrix using symbolic elements
defined through Sympy or Symengine. Symbolic computations are described via dual quaternions
in order to create compact expressions. It is possible to desribe multiple biomechanical muscle
models. At the moment, the Thelen Hill-type model is used as default. A sub-module allows
automatic convertion of OpenSim musculosqueletal models into Bioctus.

URL: https://gitlab.inria.fr/auctus-team/people/gautierlaisne/public/bioctus

Author: Gautier Laisne

Contact: Gautier Laisne

7.2 New platforms

7.2.1 Ball catcher

Participants:

Lucas Joseph.

An experimental setup was built for the RobotCup 2023 event held in Bordeaux in July. The setup
exemplifies some of the state-of-the-art algorithms developed by the team in the field of robot control,
specifically in Model Predictive Control, and also demonstrates the team’s expertise in robotics. One of

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the goals of this setup was to be comprehensible to the scientific community, industrial professionals,
and the general public. It involves a game in which the robot must catch a small ball thrown towards it in
flight. A short video and a description can be found here.

This simple game requires the ability to detect the ball in real-time during its trajectory. This is
accomplished using an OptiTrack sensor. Once the pose of the ball is determined, Model Predictive
Control is employed to calculate the robot’s trajectory to move towards the ball.

This setup was also used for other events and will be reused in the upcoming years.

7.2.2 ATROCE : Attention Tunneling and RObotic Collaboration Experiments

Participants:

Lucas Joseph, Benjamin Camblor, David Daney, Jean-Marc Salotti.

The platform consists in observing a human carrying out a task mobilizing his attention while a robot
is working in its close environment. This platform will be used to study many cognitive aspects of a
human carrying a task and how the robot can be used in such a situation.

A first set of experiment was conducted. The objective is to detect if the human is subject to an
attentional tunneling effect and propose operating strategy for the robot to minimize the operator’s entry
into this incidental mental state. To monitor the human state, an eye tracking device and a heart rate
monitoring device are used. While the human is doing a specific task, the robot must assemble several
lego towers in a determined order. When the robot doesn’t have the required lego to carry on its task, it
must wait for the human to give it the correct lego block.

A second set of experiment is being developed to extend the study of cognitive aspects of a human

carrying a task

7.2.3 MAXIFORCE: Maximal isometric force capacities measurement platform

Participants: Gautier Laisne, Lucas Joseph, Jean-Marc Salotti, Nasser Rezzoug,

Pierre Garnault.

Understanding the human force capabilities is crucial for designing physical Human-Robot Interac-
tion (pHRI) workspaces. This knowledge allows the robot to tailor its assistance, preventing the exceeding
of force limits. However, these limits vary based on the operator’s posture, muscle geometry, and bio-
mechanical properties. The experimental arrangement outlined here is crafted to measure isometric
maximal force capacities exerted in different directions by the right hand of a participant across various
postures of the right upper limb.

The experimental procedure involves the placement of motion capture markers on the upper limb
to capture posture, securing a shoulder belt to prevent translations while allowing rotations, utilizing a
custom handle affixed to a 6D force-torque sensor positioned in front of the participant on a specialized
table for handle displacement in all translations and rotations, and implementing a 3D interface to
monitor the participant’s posture and forces exerted on the handle. This interface provides visual
feedback to ensure the desired upper limb posture.

This setup is employed to create a database of maximal isometric force capacities across four dif-
ferent postures for a dozen participants. The primary objective is to gather experimental force data
for personalizing musculoskeletal model parameters to accurately replicate the forces exerted by each
participant.

7.2.4 Trajectory Modulation Platform

Participants:

Landais Erwann, Vincent Padois, Nasser Rezzoug.

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A collaboration between Auctus and Solvay aims to enhance the skills of technicians engaged in
visually classifying chemical compounds. The focus is on developing a teleoperation platform tailored to
the task, allowing technicians to perform their duties from a remote location, ensuring their safety while
leveraging their expertise for efficient task execution.

To address the challenge of ensuring a safe and responsive execution of the manual aspects of the task,
the approach involves dividing movement control into two components: path control (defining spatial
poses) and trajectory control associated with the path (managing speed and direction along the path).
This allows users to partially guide robot movements, selecting a secure trajectory type and adjusting the
real-time trajectory performed on this path.

A platform based on this concept was developed to assess its effectiveness in performing observation
tasks compared to direct manipulation. The system underwent testing across a broad range of subjects.

7.2.5 Gimbal Platform

Participants:

Landais Erwann, Vincent Padois, Nasser Rezzoug, Margot Vulliez.

Based on the findings from experiments conducted on the Trajectory Modulation Platform (see 7.2.4),
a simplified manipulator arm has been devised specifically for the task of vial movements. The chosen
design features a 3-degree-of-freedom arm, modeled after a gimbal, allowing the end-effector to execute
only rotational movements across a broad range. The arm is designed to respect task-specific constraints,
ensuring no collisions with its own components when holding the vial and avoiding obstruction of
the camera based on the position of the robot elements. This design choice ensures an intuitive and
responsive control of the platform’s movements. Although the platform lacks translational movements,
we anticipate it will deliver comparable execution times and success rates to those achieved in a live task.
Upon the completion of the development of this new platform, it will undergo additional testing with

a group of subjects in an experiment.

7.2.6 Physical ability visualisation platform based on Augmented Reality tools

Participants:

Antun Skuric, Claire Houziel, Margot Vulliez, Lucas Joseph, Vin-
cent Padois, David Daney.

Auctus has conducted initial efforts in developing a platform for the interactive visualization of various
metrics representing a robot’s physical abilities to the operator, with a specific emphasis on their polytope
representation. This visual and interactive information has the potential to offer real-time and interactive
feedback to the operator regarding the robot’s current state and physical capabilities. The overarching
goal of the testing platform is to facilitate the comparison of different visualization modalities of this
information, aiding in the understanding and evaluation of their effectiveness in diverse human-robot
collaboration scenarios.

In this preliminary stage, the emphasis is placed on immersive visualization using Augmented Reality
(AR) tools. More specifically, the initial setup revolves around a Microsoft HoloLens 2 device, chosen for
its widespread use, off-the-shelf availability, and affordability.

A brief video showcasing the platform from the operator’s perspective is publicly accessible via the

provided link. The platform is open-source, and its code is available in the GitLab repository.

8 New results

8.1 Human Factors and cognitive approaches in human/system interactions

8.1.1 Attention Sharing Handling Through Projection Capability Within Human-Robot Collaboration

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Participants: Benjamin Camblor, Lucas Joseph, Jean-Marc Salotti, David Daney,

Axel Plantey–Veux.

The link between situation awareness (SA) and the distribution of human attention, has been explored
within a human robot collaboration framework. According to (Endsley, 1995), SA is divided into three
levels: perception, comprehension and projection. It is involved in the process of making decisions and
carrying out actions in a dynamic environment. This work investigates three hypotheses. First, that the
ability to project a robot’s future actions improves performance in a collaborative task. Second, that
the more participants are involved in tasks in a collaborative environment, the better their SA will be.
Finally, that the use of a robot’s non-verbal communication motions attracts a participant’s attention
more promptly than if the robot remains motionless. A within-participants study has been designed to
investigate our three hypotheses. Participants were asked to perform a collaborative task with a robot
(Franka Emika Panda robotic arm). It required them to assist the robot at different moments while
they were engaged in a distracting task that was catching their attention (tower of Hanoi puzzle). These
moments could either be anticipated and taken into account in the human decision-making and action
loop or not. Lastly, the robot could either use non-verbal communication gestures to draw human
attention or not. The results have demonstrated the significance of considering the human capability
to project a robot next actions in their own personal attention management. Moreover, the subjective
measures showed no difference in the assessment of SA, in contrast to the objective measures, which are
in line with our second hypothesis. Finally, it seems that standing stationary can be considered a gesture
of non-verbal communication. In the present work, robot waiting was more salient in capturing human
attention when the robot remained motionless rather than making a signaling motion.This work was
accepted for publication in a journal.

8.1.2 Adaptive task sharing

Participants:

Jean-Marc Salotti.

Under the supervision of Jean-Marc Salotti, a team of 2 ENSC students, Thomas Faure and Hugo
Decroux, implemented a task sharing experiment, in which a human operator and a robotic arm (Uni-
versal Robot UR3) had to pick and place tokens on a board. As the human operator had sometimes
to be focused on another task, the robotic system was able to detect the unavoidability of the human
(unexpected delays were observed) and adapted his sharing strategy to optimize the duration of the task.
Related publications: [16].

8.1.3 Human perception of object properties

Participants:

Louis Garcia, Margot Vulliez.

Better understanding human perception could help to develop feedback strategies that better inform

a human operator during human-robot interaction, particularly in haptic teleoperation.

An experiment has been designed to study how humans perceive object physical properties of mass,
stiffness, and viscosity, and how the perception of these properties can affect the others. The first
experimental step identifies the perceptive threshold (JND) of each property individually, for a stimulus
that is generated by a haptic device during a controlled back-and-forth user forearm motion. Two
methodologies (constant and psychological) are implemented to extract the JND from collected data.
The second experiment presents stimuli that simulate a combination of properties, to extract the impact
or bias of the combination on each property perception.

This project, that was done in collaboration with the CeRCA (University of Poitiers), unfortunately

stopped after the PhD student resignated for personal reasons, before the experiment was carried out.

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8.2 Human Behavior Analysis

8.2.1 Holistic view of Inverse Optimal Control by introducing projections on singularity curves

Participants:

Jessica Colombel, David Daney, François Charpillet.

Inverse Optimal Control (IOC) is a framework used in many fields, in particular robotics and human
motion analysis. In this context, various solution methods have been proposed in the literature. This
work introduces a new approach, Projected Inverse Optimal Control (PIOC), which offers a simple yet
comprehensive view of inverse optimal control methods. In particular, we explain how uncertainties
can be properly handled from our perspective. Thus, this work highlights how classical methods can be
understood as trajectory projections in the solution space of the underlying direct optimal control (DOC)
problem. This perspective makes it possible to examine projections other than classical methods, which
can be fruitful for researchers in this field. Related publication: [15]

8.2.2 Improvement of the robustness of the projected inverse optimal control problem

Participants:

Ahmed-Manaf Dahmani,
François Charpillet.

Jessica Colombel, David Daney,

A thorough exploration of the recent findings previously presented on Inverse Optimal Control (IOC)
is currently underway as part of a thesis initiated in December 2023, following a master’s internship.
This study encompasses several crucial aspects. Firstly, we analyze the polynomial representation of
trajectories, assessing its impact on the complexity and precision of the IOC problem. We examine and
compare various types of projections onto singularity curves, proposing new methods to provide diverse
characterizations of the uncertain IOC problem. Additionally, we explore strategies to mitigate high
numerical errors, with a particular emphasis on normalizing cost functions.

8.2.3 Study of Motor Variability

Participants:

Raphael Bousigues, David Daney, Vincent Padois.

The study of motor variability enables us to understand human strategies for carrying out a movement:
it gives indications of an operator’s state, particularly when interacting with a robot. To verify this
hypothesis, we set up an experimental device that constrains the degrees of freedom of a human arm
through a loop of physical wire to be followed and its observation by a motion capture system. This year,
we had 18 subjects complete a course of curves and straight lines in a variety of conditions. The results
are currently being processed.

8.2.4 Observing and recording information on an expert task

Participants:

Erwann Landais, Vincent Padois, Nasser Rezzoug.

Within the framework of the study of the possible contributions of a semi-autonomous system for the
realization of an expert task in the chemical industry, the question arose of identifying the components of
the expertise expressed by the operator carrying out this task. To this end, several contacts were made
with different operators, in the form of interviews and video recordings of demonstrations. Thanks
to these interviews, the components of the expertise expressed by the operators could be highlighted
(manual, visual and cognitive expertise), as well as a more general definition of the problematic linked to

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this task (manipulation of objects in the context of a visual classification task). This information opened
up different lines of research concerning possible semi-autonomous assistances to help experts to carry
out a task.

An experiment validated by INRIA’s ethics committee was carried out to test the capabilities of the
Trajectory Modulation Platform for performing a visual classification task. This experiment consisted
in reading words printed on four white capsules (dimensions 6 x 12 mm) placed into cylindrical vials (
dimensions 16 mm x 70 mm). Four randomly selected vials were tested by each variant. Firstly, users
had to perform the task via direct handling, then under conditions secured by a protection barrier. Users
were then invited to perform the task using different trajectory modulation variants (modulation and
passive viewing of a pre-recorded video, modulation of the trajectory of a Franka-Emika Panda robot
performing the task in real time in front of a monocular Logitech Brio 4K camera). After each trial of
a variant, users evaluate different aspects of this variant (manual and visual performance, ease of use,
acceptability of the interface) through a questionnaire. During the trials, various objective criteria are also
measured (number and nature of interaction with the interface, time and degree of success in the task,
physical posture of subjects to determine postural comfort using ergonomic metrics). This experiment
was carried out with 37 subjects (age : 27±5, 20 females). The data recorded showed that the proportion
of successes, as well as the subjects’ perceptions of visual performance, comfort of use and acceptability
of the interface, were similar and high for all the variants. This suggests that this task is indeed achievable
via the proposed interface. However, data also showed that average task completion times when using the
trajectory modulation variants were significantly higher than handling by hand variants, which implies
that the proposed remote semi-automatic control procedure fails to achieve satisfactory performance
regarding execution time. An interface allowing more reactive manipulation of the vial’s movements
seems necessary, and will be tested in a future experiment.

8.2.5 Searching for best-fitting musculoskeletal models approximating an individual’s upper limb

force capacities

Participants: Gautier Laisné, Jean-Marc Salotti, Nasser Rezzoug.

Derivative-free algorithms for force polytopes prediction In biomechanics, human hand force capacit-
ies refer to the set of feasible forces exertable at the hand considering arm posture and muscle tensions.
In physical Human-Robot Interaction (pHRI), knowing the operator’s force capacities allows the robot to
adjust its assistance to avoid exceeding force limits. Using a musculoskeletal model representing a human
upper-limb, force capacities can be described as a 3D polytope called the force polytope. This work
explores, in silico, force polytopes computed in three postures to personalize a musculoskeletal model
through a non-differentiable and non-convex optimization problem. In order to solve this optimization,
derivative-free algorithms have been used. They learn a model distribution in the search space and uses
sampling to understand the function topology, allowing local researches to give better solutions, without
assuming the function to be differentiable: in genetic algorithms, the model is a set of good solutions
and the sampling is done through variations on solutions; and in SRACOS, the model is a hypercube
and the sampling is from the uniform distribution in the hypercube. It learns to classify solutions as
either positive or negative, using reinforcement learning described as a Markov decision process. The
solutions are then sampled from the positive areas. In average for all initial generations, the best polytope
prediction comes from the solution found by the genetic algorithm for the polytope representation in 26
vertices. SRACOS tends to overfit more than genetic algorithms. Related publications: [9, 17]

Gathering of upper-limb maximal isometric force exertion associated with motion capture data An
experimental setup has been designed to gather 26 maximal isometric force exertion at the right hand of
a participant in 4 different postures. The setup ensures stability of the shoulder as well as minimizing
the exertion of lower-limb muscles. Ten subjects participated to the experiment between October and
December 2023, during two 3-hour sessions. The gathered data consists of force exertions acquired from

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a force-torque sensor as well as a scaled upper-limb musculoskeletal model with joint angles obtained via
motion capture. It will be used as input for musculoskeletal model personalisation of muscle parameters.

Analytical expression for force polytope via Minkowski sums of superquadrics When measuring
a subject’s maximal force capacities in specific direction, we can suppose that we measure points at
the surface of a polytope. The aim of this research was to express analytically these points, in order
to parametrize a musculoskeletal model which would generate force polytopes fitting the measured
points. The surface of a force polytope is described as the surface of torque zonotope intersected with the
joint configuration’s null space. Besides, the torque zonotope has great geometrical properties, thus it is
possible to describe its surface via Minkowski sum of superquadrics (a generalization of ellipsoids which
have simple analytic expression). First results were in 2D and lead to a smooth analytic expression

Novel description of force capacities: the force ovoid The set of isometric maximal forces of an operator
can be geometrically treated through the study of force polytopes, usually described by its vertices. In
static, these polytopes arise from intersecting the image of the jacobian transpose of a musculoskeletal
model with the torque zonotope, which is the projection of the muscle tension space onto the torque
space. However, computing such polytopes requires computational resources, even when approximating
its vertices via the Iterative Convex Hull algorithm ([57]). A new approach suggests that when the muscle
tension space is of a much higher dimensionality than the torque space, the produced torque zonotope
resemble a smaller ellipsoid. An empiric formula has been established to express an ellipsoid dilation
coefficient, which depends only on the tension space dimension and the mean feasible maximal tensions.
This new representation of torque capacities led to a new force capacities representation created from
the intersection of an ellipsoid and an affine space: an ovoid. This will be used as a new method for force
capacities prediction, but also as a tool to better understand the impact of the muscle geometry and
tensions to produce forces at the hand in the upper-limb.

Force polytope with constraints integration This work tackled two important points related to force
polytope definition based on musculoskeletal models not taken into account in the available models. The
first is the inherent instability of the gleno-humeral joint of the upper-limb prone to dislocation in case of
important shear joint reaction force at this joint . The second one concerns the definition of the maximal
force polytope taking into account movement dynamics and gravity. For both points, the original Iterative
Convex Hull Method [57] was upgraded by modifying the vertex search linear programming problem of
the ICHM with specific constraints. Simulation results attest the validity of these adaptations. Related
publications:[27, 12]

Maximum upper-limb joint actuation: SimACT This work conducted with Jonathan Savin (INRS)
aimed at providing an estimate of maximum joint torque actuation at the upper-limb elbow and shoulder.
These data are needed for workplace ergonomic assessment in the framework of digital modeling tools
(Delmia, Jack...). The approach taken consisted in using a musculoskeletal model and to infer the
maximum joint actuation by resorting to polytopic representations. Related publications:[10]

8.3 Human Robot Interaction

8.3.1 A coupled view of the physical abilities of human-robot dyad for the online quantitative evalu-

ation of assistance needs

Within the framework of Antun Skuric PhD thesis [22] (BPI Lichie Project 10.4), we pursued our work aim-
ing at efficiently and accurately characterizing both human and robots physical abilites. Our contribution
in this domain over the laster year is three-fold.

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Online approach to near time-optimal task-space trajectory planning for collaborative robots Con-
forming to safety standards often imposes limitations on the performance and size of collaborative robots,
making their applications only viable if fully exploiting their abilities. When it comes to planning for these
robots’ motions in human environments, there is often a trade-off to be made between the planning the
optimal trajectories, which exploit their full movement potential, and the real-time responsiveness to the
unexpected events in these dynamic and unstructured spaces. Traditional reactive trajectory planning
methods, in order to be used online use simplified robot model, often over or underestimating robot’s
abilities. On the other hand, traditional methods that do exploit robot’s abilities optimally have significant
computational complexity and require being computed in-advance, not allowing for reactivity.

This method aims to bridge this gap, by introducing a method able to plan robot’s trajectories that
exploit its full motion abilities in real-time. The proposed online re-planning method in each step of
trajectory execution 1) evaluates robot’s movement ability in trajectory direction using an efficient tools
from polytope algebra 2) calculates a time-optimal Trapezoidal acceleration profile (TAP) trajectory using
the updated limits.

The method is compared against a state-of-the-art time-optimal joint-space planning method TOPP-
RA and a classical reactive strategy, based on task-space TAP planning. Results show that the proposed
method has a comparable trajectory execution time as TOPP-RA, while exploiting the robot’s movement
capacity better and having lower tracking error than the traditional TAP approach. A mockup experiment
is presented where the proposed method is used for collaborative waste sorting using a Franka Emika
Panda robot, showing the efficiency of the approach in a practical application.

Sampling-based non-convex approximation of the robot’s reachable space This work introduces a
preliminary work on the sampling-based reachable space approximation strategy within a horizon time
of interest for robotic manipulators. This method builds on the previously introduced approach [56], and
allows it to account for the robot’s non-linear kinematics and allows the non-convex characterisation
of the robot’s reachable spaces. Therefore, the proposed method has a potential to provide an accurate
characterisation of robot’s reachable space. Robot’s reachable space is valuable information both for the
robot’s motion planning and for the operator’s understanding of the robot’s physical abilities. However,
at this stage this strategy lacks formal guarantees on its approximation accuracy, necessitating further
research to enhance reliability and information quality conveyed to operators.

This sampling based method is publicly available as an open-source gitlab repository. Additionally,
this algorithm will be a part of the upcoming release of the Pinocchio library confirming the interest of
the robotics community in this approach.

8.3.2 Prediction of pose errors implied by external forces applied on robots: towards a metric for the

control of collaborative robots

Participants:

Vincent Fortineau, Vincent Padois, David Daney.

In [25], we tackle the question of quantifying the pose deviations of robots subject to external disturb-
ance forces. While this question may not be central when considering large robots perfectly rejecting
disturbances through high controller gains, it is an important factor to consider when considering collab-
orative settings where smaller robots may be deviated from their task because of unmodeled physical
interactions. This is all the more true when considering human-robot collaboration where human capa-
cities may fluctuate over time and have to be compensated by a proper adaptation of the robot control. To
move forward in this direction, this works first derive a deviation prediction methodology and exemplifies
it using three largely employed control approaches. The proposed prediction method is then validated
using simulated and real robot experiments both in single and multiple robots cases. The obtained results
constitute a stepping stone towards a quantitative metric for robot adapting their behaviour to human
motor fluctuation.

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8.3.3 Re-expression of manual expertise through semi-automatic control of a teleoperated system

Participants:

Erwann Landais, Vincent Padois, Nasser Rezzoug.

An experiment validated by INRIA’s ethics committee was carried out to test the capabilities of the

Trajectory Modulation Platform for performing a visual classification task.

This experiment consisted in reading words printed on four white capsules (dimensions 6 x 12 mm)
placed into cylindrical vials ( dimensions 16 mm x 70 mm). Four randomly selected vials were tested by
each variant. Firstly, users had to perform the task via direct handling, then under conditions secured by
a protection barrier. Users were then invited to perform the task using different trajectory modulation
variants (modulation and passive viewing of a pre-recorded video, modulation of the trajectory of a
Franka-Emika Panda robot performing the task in real time in front of a monocular Logitech Brio 4K
camera). After each trial of a variant, users evaluate different aspects of this variant (manual and visual
performance, ease of use, acceptability of the interface) through a questionnaire. During the trials,
various objective criteria are also measured (number and nature of interaction with the interface, time
and degree of success in the task, physical posture of subjects to determine postural comfort using
ergonomic metrics).

This experiment was carried out with 37 subjects (age : 27±5, 20 females). The data recorded showed
that the proportion of successes, as well as the subjects’ perceptions of visual performance, comfort of
use and acceptability of the interface, were similar and high for all the variants. This suggests that this task
is indeed achievable via the proposed interface. However, data also showed that average task completion
times when using the trajectory modulation variants were significantly higher than handling by hand
variants, which implies that the proposed remote semi-automatic control procedure fails to achieve
satisfactory performance regarding execution time. An interface allowing more reactive manipulation of
the vial’s movements seems necessary, and will be tested in a future experiment.

8.3.4 Haptic guidance to assist human motion

Participants:

Alexis Boulay, Margot Vulliez, David Daney.

This work is within the framework of the collaboration with the Farm3 company, which aims at
developing a telerobotic system based on shared autonomy for the remote nurturing of plants in a
controlled chamber. Performing remote tasks through the teleoperation system can be assisted through
haptic guidance to increase performance, safety, and comfort of the user. Several axis were studied in this
direction:

• State-of-the-art on haptic guidance: Also known as virtual fixture, active constraint or virtual guide,
a haptic guidance is a virtual geometric constraint used to generate a force feedback that help
the user to follow a given behaviour (task trajectory, safety area,...). The different definitions are
strongly linked to the tasks studied, whether surgery, navigation or pick-and-place. They also are
not limited to teleoperation but can be used on physical human-robot interaction or programing
by demonstration. This task dependency highlights that there is no unified formalism to model
haptic guidance. However, common computation methods can be identified for the generation of
the guidance force, such as the use of spring-damper models (SD), the definition of potential fields
(PF) or the establishment of restrictive zones with guiding tubes (GT).

• Definition of a generic haptic guidance expression, the ruling guidance (RG): the RG model is
proposed to encompass common haptic guidances from the literature in a unique expression. It
allows a continuous switch between these generic methods, through only few parameters, and an
exploration of intermediate guidance states.

• Implementation of a modular teleoperation bilateral controller 7.1.8 with the active-constraint
module 7.1.7 which integrates the standard haptic guidance (SD, PF, GT) and the proposed generic
and parameterized ruling guidance (RG).

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8.4 Robotics and control

8.4.1 Predictive Control of Collaborative Robots in Dynamic Contexts

Participants: Nicolas Torres, Antun Skuric, Vincent Padois, Lucas Joseph,

David Daney.

Within the framework of Nicolas Torres PhD thesis (CIFRE Stellantis), we have continued explor-
ing control architectures allowing for the online adaptation of robot motion when facing dynamically
changing contexts where constraints and tasks to be achieved can evolve at all time. This led to several
contributions on the theoretical [28] [23], experimental (cf. video here) and software 7.1.6 side of Model
Predictive Control, formulated here in a linear fashion over SE (3)

8.4.2 Model Predictive Control for shared human-robot tasks

Participants:

Elio Jabbour, Margot Vulliez, Vincent Padois.

Shared control emerges as a solution to improve conventional teleoperation through robotic assitance.
It combines human and robot capabilities in a unified command, which could overcome limitations
in both autonomous robots and fully teleoperated robot. We focus on shared control methods, and
specifically:

• define two computation methods of the authority level (impact of each agent on the action),
respectively based on the human activity and proximity to the task target. The resulting authority
levels are, then, given by assigning fixed weights on both the activity or proximity factors, for each
task’s state of a pick-and-place scenario.

• formalize the equations of a shared-control paradigm that compute the desired robot motion (pose
an twist) based on model predictive control (MPC). It optimizes and predicts the robot motion on a
horizon, given the human and automation (planned automated trajectory) motion inputs and the
authority levels, while respecting robot and human limits and environmental constraints. We are
currently implementing and testing this MPC approach, and will compare it to conventional linear
blending methods.

• propose a tool 7.1.5 to optimize the hyperparameters of a MPC framework thanks to a genetic
algorithm (NSGA-II). It helps tuning the MPC parameters, such as the prediction time horizon,
the velocity coefficient, and the control input weigth, based on objective functions that maximize
the system-response rise time, minimize the steady-state error, and minimize the overshoot ratio,
under a fixed computational-time constraint.

8.4.3 Criteria for evaluation of serial and parallel robot leg

Participants:

Virgile Batto, Margot Vulliez.

The legged-robot codesign PhD project, in collaboration with the Gepetto team at LAAS-CNRS, aims at

developing AI-based tools to help in designing a new leg architecture for a dynamic walking robot.

Several criteria to characterize the design of bipedal legs have been introduced. They aim to guide
the design choices and could be implemented in a codesign approach. They reflect the leg’s overall
performances (ability to produce dynamic and accurate foot movements, absorb impacts, and lower the
motor torques needed to stand up) and characterize the design’s compactness.

We give the algorithmic formulations to evaluate these criteria beyond classical serial designs to
account for any parallel mechanisms. To validate these formulations, we developed a library of open-
source CAD models describing the main existing biped architectures. We compute and discuss the

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comparative performances of the architectures in the leg-model database. We hope this study can serve
as a baseline to better design future biped robots.

Related publication: [14]

8.4.4 Optimization of a novel parallel leg architecture

Participants:

Virgile Batto, Margot Vulliez.

Dynamic bipeds can comprise parallel mechanisms in their leg kinematics to relocate the actuators
close to the hip and reduce the weight of moving parts. Such parallel mechanisms must be finely
optimized that the robot meets the required capabilities to perform different locomotion tasks.

A new parallel leg architecture has been proposed and is currently optimized. This work is based on
the software we developed for Closed Loop Architecture Optimisation Cleo. It also serves to improve
the software. Cleo is an optimizer that takes as input the conceptual architecture design of the leg and
returns a set of optimized solutions for the mechanical architecture by using a genetic algorithm.

The main objective of our design optimization is to generate the most dynamic leg possible with
the given architecture, under different task requirements and geometric and kinematic constraints. We
specifically minimize the effective inertia of the foot and maximize the impact mitigation factor of the
leg. A prototype of the leg will be fully designed and built in the future to experimentally validate the
optimized architecture.

8.4.5 Elasto-Geometric Calibration of a TALOS Humanoid Robot

Participants: David DaneyVincent Bonnet .

This result shows our work on robot calibration in collaboration with LAAS, CNRS. Elasto-geometric
calibration of the whole body of humanoid robots is essential, particularly for their accurate control
and simulation. We have proposed a new method which has been validated on a TALOS. It enables
rapid, accurate whole-body calibration. The proposed approach has been cross-validated experimentally.
Related publication: [7]

8.4.6 Solving semi-constrained end-effector path planning problems

Participants: Guillaume De Mathelin De Papigny, Vincent Padois.

Within the framework of the Plan de Relance with the SME Aerospline, we have mostly worked
on proposing a compuationally efficient algorithm to solve semi-constrained end-effector path plan-
ning problems. Solving these problem is crucial to find motion solution for robots evolving in highly
constrained environements while presenting some level of task redudancy.

8.4.7 Real time jogging respecting robot and task constraints

Participants:

Sébastien Dignoire, Vincent Padois.

Auctus and Fuzzy Logic Robotics have been working together on the development of new methods
for generating movement in industrial robotics thanks to optimization problem with constraints. These
methods based on the resolution of quadratic programming problems allow to generate trajectories
respecting the limits of the robot and the constraints of the task. For example, we implemented an online

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mouse jogging that allows the operator to control the robot in 6 dimensions exploiting the knowledge of
the robot’s state and its capacities.

9 Bilateral contracts and grants with industry

9.1 Airbus

Participants: David Daney, Vincent Padois, Antun Skuric.

The collaboration aims to design a constellation of mini-satellites and one of the challenges is to
rethink their production, in particular through robotic assistance of operators. In this project, we have
developed a coupled model of human-robot physical capabilities, see 10.4.

Project in a nutshell:

• Consortium : AUCTUS@Inria, Airbus

• Funding : BPI

• Duration : 2020 – 2024

9.2 Stellantis

Participants: David Daney, Vincent Padois, Nicolas Torres.

The objective of this project is to work on the required principles to avoid the classic restrained static
security zones, synthesizing a dynamic representation of the shared workspace to take advantage of state
of the art control laws, allowing a fluid collaboration between human-robot. This dynamic synthesis
requires knowledge of the robots state (geometric, cinematic and cognitive, such as fatigue, expertise and
situation awareness), its tasks, capacities, state of humans that surround it and their tasks. Furthermore,
it needs to achieve a formal and provable online algorithm that correctly estimates the state of the
human and guarantee a safe shared workspace tackling ambitious scientific questions poorly addressed
in literature.

Project in a nutshell:

• Consortium: AUCTUS@Inria, PSA Automobiles

• Funding: PSA Automobiles, ANRT (CIFRE)

• Duration: 2020–2023

9.3 Solvay

Participants:

Vincent Padois, Nasser Rezzoug, Lucas Joseph, David Daney, Er-
wan Landais.

Since 2020, we have developed a long term collaboration with the chemical company Solvay in order
to help them in the digitalization and robotization of their productions. Our interlocutors are researchers
of their Laboratory Of the Future (LOF) on the theme of collaborative robotics, seen as an important
way to assist their operators and secure their potentially dangerous actions. The first objective is to
develop a cobotic solution to follow an operators’ work step by step by proposing an assistance available
at the user’s request in a constrained environment. This project has led to a bilateral contract and to the
participation in the ANR Pacbot. In addition, in 2021, we are participating in the Miels project (see 10.5)

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Inria Annual Report 2023

in order to cobotize a handling task for the mixing of chemicals that requires human gestural expertise.
The difficulty is first to learn from the human and then to synthesize this expertise.

Project in a nutshell:

• Consortium: AUCTUS@Inria, Solvay

• Funding: Région Nouvelle-Aquitaine, ANR, Solvay, CNRS

• Duration: 2020 - 2024

9.4 Farm3

Participants:

Alexis Boulay, David Daney, Margot Vulliez.

We collaborate with Farm3, a start-up company specialized in vertical farming, since 2020. The
company develops a robotized vertical farm, the Cube, to grow plants in a controlled environment
through ultrasound-based techniques. Agronomists and farmers can remotely act on the plants through
a teleoperation system, to perform expert tasks (seedlings, pollinating flowers, measuring data...) without
polluting the sensitive growth environment.

After preleminary results of a master’s internship in 2021, a contract was signed with Farm3 in 2022
to start a PhD project. The PhD thesis aims at developing co-control approaches to assist the agronom-
ists/farmers in teleoperated vertical agriculture. We first analyze specific farming tasks, to automate the
simpler ones (moving a pot, taking pictures of the plants, ...) and determine the expert actions that must
be preserved. We develop assistive control methods, based on haptic guidance, to help the operator
to perform the remote tasks through proper feedback. We specifically focus on task/environement
variability and constraints and user preference to adapt the guidance to increase performance, comfort,
and safety of the teleoperation.

Project in a nutshell:

• Consortium: AUCTUS@Inria, Farm3

• Funding: Farm3, ANRT (CIFRE)

• Duration: 2022–2025

9.5 Aerospline

Participants: Guillaume De Mathelin de Papigny, Vincent Padois, Lucas Joseph.

Started in 2021, the partnership between AUCTUS and the robotics company Aerospline has two main
objectives. On the one hand, the collaboration brings to Aeropline new scientific research knowledge
in Robotics in order to develop new robotic methods and tools for their projects. On the other hand, it
brings to AUCTUS elements for the formulation of new scientific problems.

Project in a nutshell:

• Consortium: AUCTUS@Inria, Aerospline

• Funding: Plan de Relance

• Duration: 2021-2023

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27

9.6 Fuzzy Logic Robotics

Participants:

Sébastien Dignoire, Vincent Padois.

Started in 2022, the partnership between AUCTUS and the robotics company Fuzzy Logic Robotics
has two main objectives. On the one hand, the collaboration provides Fuzzy Logic Robotics with a way to
evaluate the pertinence of state of the art knowledge in robotics in their daily robotics practice. On the
other hand, it brings to AUCTUS elements for the formulation of new scientific problems.

Project in a nutshell:

• Consortium: AUCTUS@Inria, Fuzzy Logic Robotics

• Funding: Plan de Relance

• Duration: 2022-2024

10 Partnerships and cooperations

10.1 International initiatives
Shared Haptics for Augmented Assistive Robot Expertise (SHAARE)

Participants: Kwang-Hyun Lee (Postdoc), Donghyeon Kim (PhD), Seong-Su Park
(PhD), Jee-Hwan Ryu (Full Professor, IRiS@KAIST), Alexis Boulay, Vin-
cent Padois, David Daney, Margot Vulliez.

A collaboration has been initiated with the IRiS lab at KAIST, to share our complementary methodolo-
gical orientations in haptic shared control. We develop shared-control approaches that, either, better
guide the human through adaptive haptic guidance, or adjust the robot behavior according to the human
gestures. The IRiS lab develop virtual-fixture feedback from a task description given by the user. They also
study machine learning strategies to transfer skills from the human to the robot in haptic teleoperation.
The Auctus team focuses on the core problem of shared control under safety, human-centered, and
task/environement constraints. They build upon model-based optimization problems to both generate
the force feedback from virtual guidance and the robot command from the joint human inputs and robot
skills.

These different approaches should together form a comprehensive shared haptic framework, where
the human is guided toward optimal gestures and helped by the robot taking more autonomy on the task.
This collaboration specifically aims at augmenting the robot assistive behavior in haptic teleoperation by
simultaneously improving haptic guidance and transferring expert skills to the robot. The works focuse on:
1.Generating optimal virtual fixtures from the task semantics, user preferences, and robot/environment
constraints; 2. Developing robust and adaptive robot assistive skills, modeled through task-oriented
force-motion control primitives; 3.Transferring expert skills from the human operator to the robot during
the interaction.

Project in a nutshell:

• Consortium: KAIST (IRiS lab, Daejeon, South Korea), AUCTUS@Inria

• Funding: None

• Duration: 2023 - ongoing

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Inria Annual Report 2023

Design and control solutions for compact haptic device

Participants:

Adrian Piedra (PhD), Mikael Jorda (Consultant Researcher), Ous-
sama Khatib (Full Professor, AI lab@Stanford), Margot Vulliez.

This collaboration continues the works initiated in the past with the Stanford Robotics Lab, to develop
a new compact haptic device. We are interested in improving some mechatronic design aspects to
increase the device performance, such as the motors’ drive controller or the gripper integration inside the
handle. We together propose workspace mapping algorithms and control solutions for such a compact
parallel architecture, that are tested within the sai2 simulation tool of the Stanford Robotics Lab and
implemented on the developed prototype. Several visits to the Auctus team and at Stanford University
have been done this year to boost collaborative progresses.

Project in a nutshell:

• Consortium: Stanford University (AI lab, Stanford Robotics, USA), AUCTUS@Inria

• Funding: None

• Duration: 2022 - ongoing

Improved Bearings-only Target Motion Analysis Using AI Tools (IMAnAI)

Participants: David Daney, , Fançois Charpillet.

The aim is to re-examine BOTMA (bearings-only target motion analysis) scenarios using new ap-

proaches from control and estimation theory or artificial intelligence.

Project in a nutshell:

• Consortium: Inria, IIT Delhi, Naval Group

• Funding: Inria, IIT Delhi, Naval Group

• Duration: 4 years

10.2 International research visitors

10.2.1 Visits of international scientists
Other international visits to the team

Participants: Mikael Jorda, Ludovic Righetti, Philip Long.

• Mikael Jorda

Status Consultant Researcher

Institution of origin Stanford Robotics lab, AI lab, Stanford University

Country USA

Dates 11th-13th September and 21st-23rd November 2023

Context of the visit Technical works on motor control and cogging compensation for the co-
developed haptic device. Simuations and tests of haptic controllers on our experimental
platform.

Mobility program/type of mobility Collaborative works on haptics, Stanford Robotics lab funding

Project AUCTUS

29

• Ludovic Righetti

Status Associate Professor

Institution of origin NYU, Machines in Motion lab, New York

Country USA

Dates 23rd-24th October 2023

Context of the visit PhD defense jury of Nicolas Torres, invited talk "Learning to optimize dynamic

behaviors", collaboration with Vincent Padois

Talk Learning to optimize dynamic behaviors video

Mobility program/type of mobility PhD defense jury

• Philip Long

Status Lecturer

Institution of origin Atlantic Technological University, Galway

Country Ireland

Dates 6th-7th November 2023

Context of the visit PhD defense jury of Antun Skuric, invited talk "Facilitating Human Robot Col-
laboration by making Robot’s smarter", collaboration with Vincent Padois and Antun Skuric

Talk Facilitating Human Robot Collaboration by making Robot’s smarter

Mobility program/type of mobility PhD defense jury

10.2.2 Visits to international teams

Research stays abroad

Participants: Margot Vulliez.

Visited institution: Stanford Robotics lab, AI lab, Stanford University

Country: USA

Dates: 5th-17th October 2023

Context of the visit: Transporting and setting-up in the lab experimental room the prototype of a haptic
device we co-developed, planning future works in electronic and control to improve the current
design.

Mobility program/type of mobility: Collaborative works on haptics, Stanford Robotics lab funding

10.3 European initiatives

10.3.1 Other european programs/initiatives

Impact Aware Robotics

Participants:

Alessandro Saccon (Associate Professor, ME Dept, Dynamics and Con-
trol Group, Eindhoven University of Technology (TU/e)), Marco Mor-
ganti (Technical leader at Franka Robotics), Vincent Padois.

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Inria Annual Report 2023

Aside the IAM European project, this informal scientific collaboration aims at improving impact
models and the prediction of the behaviour of robots making desired or non desired impacts with their
environment. This is foreseen as a necessry condition in order to better control these complex and
essential transitions. This collaboration has led to several modelling, simulation and experimental
campaigns among which the most recent one was led in collaboration with Franka Robotics, one of the
European leader in collaborative robotics.

Project in a nutshell:

• Consortium: TU Eindhoven, AUCTUS@Inria, Franka Robotics

• Funding: None

• Duration: 2017 – ongoing

10.4 National initiatives
Parametrisation of robotic actions by demonstration

Participants:

Julie Dumora, Olivier David (CEA LIST), Vincent Padois.

Intuitive programming is a field of research in robotics aimed at reducing time and expertise required
for programming a robotic system. In this context, this project and the associated internship has focused
on programming robotic actions based on semantic data. This semantic data symbolically describes
objects of interest and their relationships in a language easily interpretable by a human. The goal is to
create a repository of actions described semantically, which can be reused in a new context to program
the robot. Actions are learned through demonstration, meaning they are performed directly with the
robot. The pertinence of the proposed approach has been demonstrated experimentally on a set-up at
CEA List in Bordeaux.

Project in a nutshell:

• Consortium: CEA LIST, AUCTUS@Inria

• Funding: None

• Duration: 2023

BPI LiChIE

Participants:

Antun Skuric, David Daney, Vincent Padois.

The LiChIE project (funded by BPI) aims to design a constellation of mini-satellites for optical Earth
observation. Among many other topics, this requires to rethink the way sattelites are being produced in
order to ease this highly complex process. There is actually an unprecedented economical and societal
demand for robots that can be used both as advanced and easily programmable tools for automatizing
complex industrial operations in contexts where human expertise is a key factor to success and as assistive
devices for alleviating the physical and cognitive stress induced by such industrial task. Unfortunately, the
discrepancy between the expectations related to idealized versions of such systems and the actual abilities
of existing so-called collaborative robots is large. Beyond the limitations of existing systems, especially
from a safety point of view, there are very few methodological tools that can actually be used to quantify
physical and cognitive stress. There is also a lack of formal approaches that can be used to quantify the
contribution of collaborative robots to the realization of industrial tasks by expert operators. Of course,
in the state-of-the-art, existing works in that domain do consider some aspects of the current state of
the operator in order to propose an appropriate robot behaviour. One of their conceptual limitations is
to consider an a priori defined human-robot collaboration scenario where the expertise of the human

Project AUCTUS

31

operator is of importance but limited to a single operation. The consideration of larger varieties of tasks is
rarely considered and, when it is, only a strict separation of the tasks to be achieved by each member of the
human-robot dyad is considered. In this project, we propose to develop a coupled model of human-robot
physical abilities that does not make any a priori with respect to the type of assistance. This requires to
develop a parameterisable generic model of the potential physical link and implied constraints between
the human operator and the robot. This model should allow to describe the task to be achieved by the
human alone or using a collaborative robot through different interaction modalities. Online simulation
of these scenarios coupled with ergonomic and performance indicators should both allow for the discrete
choice of the right assistance mode given the task currently being achieved as well as for the continuous
modulation of the robot behaviour.

Project in a nutshell:

• Consortium: AUCTUS@Inria, Airbus, Erems, iXblue, TEAMS@Inria, Onera

• Funding: BPI

• Duration: 2020 - 2023

• Researchers involved: Antun Skuric (PhD Student), Vincent Padois (thesis advisor) and David

Daney (thesis advisor)

ANR PACBOT

Participants: David Daney, Jean-Marc Salotti, Benjamin Camblor, Loïc Mazou.

The general objective of the project is to design a semi-autonomous cobotic system for assistance,
able to choose, synchronize and coordinate tasks distributed between humans and robots by adapting
to different types of variability in professional gestures, all by anticipating dangerous situations. The
orchestration of tasks between a man and a robot is difficult because it must answer the question of the
distribution of roles within the couple according to physical and decision-making skills and constraints
as well as the consequences of their interactions. However, we cannot put the two actors at the same level:
the robot has to adapt its actions to the work of an operator and, more precisely, to its motor and cognitive
strategies that materialize through the quantifiable variability of professional actions. On the other hand,
the very interest of the robot is to assist the operator in his phases of fragility while preserving his physical
and mental integrity, in particular considering that human error is inherent in operator action. These
considerations are, for Pacbot, the conditions necessary for the joint achievement of efficient work.

Project in a nutshell:

• Consortium: AUCTUS@Inria (Team Leader, David Daney - principal investigator), Laboratoire

Informatique de Grenoble, Laboratoire Interuniversitaire de Psychologie (Lyon)

• Funding: ANR Funding (246 240 Euros for Auctus)

• Duration: 2021 - 2024

ANR JCJC ASAP-HRC

Participants: Célestin Préault (Postdoc), Jean-Pierre Gazeau (Research Engin-
eer CNRS, RoBioSS@Pprime), Cécile Scotto (Interactions@CeRCA),
Elio Jabbour, Vincent Padois, Margot Vulliez.

A young-researcher ANR grant was obtained in 2021 to start a collaborative project between the
AUCTUS team at Inria, the RoBioSS team at the Pprime Institute (CNRS), and the CeRCA laboratory
(CNRS). It aims at rethinking autonomy for shared action and perception in Human-Robot Collaboration,
through transverse studies in robotics and cognitive sciences. More particularly, three scientific axes

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Inria Annual Report 2023

must be addressed to develop a human-centered and generic shared-autonomy framework: 1) study
key features of Human-Robot perception-action mechanisms and identify multisensory integration
processes involved in Human-Robot interaction. These human studies should constitute the baseline of
robotic developments and shape the shared-autonomy scheme; 2) develop a shared perception between
the different actors (humans and collaborative robots), according to their sensory data and involvement
in the task. This shared perception will be based on a multimodal (haptic, visual) feedback mixture
conveying information about the task, the environment, and the collaborators; 3) combine Human-Robot
commands into a joint action toward the task goal. The human inputs will first be used to infer the
operator intent and adapt the robot behavior. Then, the shared action will combine robot skills and
human commands into a unified and consistent control objective.

Project in a nutshell:

• Consortium: AUCTUS@Inria (coordinator - Margot Vulliez), RoBioSS@Pprime (CNRS), Interac-

tions@CeRCA (CNRS)

• Funding: ANR Funding (287 840 Euros)

• Duration: 2021 - 2026

LAAS-AUCTUS collaborations

Participants:

Thomas Flayols (Research Engineer CNRS), Nicolas Mansard
(Senior Researcher CNRS), Vincent Bonnet (Associate Professor, GE-
PETTO@LAAS), Virgile Batto, Margot Vulliez, David Daney.

We have built a close scientific relationship with the Gepetto team at LAAS CNRS (Toulouse) these

past few years, through several collaborative projects:

• Humanoid robot calibration: A collaboration on problems of elasto-geometric calibration of

humanoid robots has been carried out (see 8.4.5).

• Inverse Optimal Control: A collaboration on Inverse Optimal Control problem has started in

pursuit of the results obtained in 8.2.1.

• Legged-robot codesign: This PhD project aims at developing a generic codesign approach which
will cover the hardware specification and dimensioning and the control strategy and requirements
at once. We propose to leverage mastered AI-based methods (simulation, planning, optimization)
to guide the mechatronic design cycles and to provide tools to assist designers. The transversal
approach will be applied to the codesign of a new dynamic legged robot, as a balance between
versatile but heavy robots (Atlas, Talos) and light robots limited to walking (Digit). First results of
this PhD project are presented in 8.4.3 8.4.4.

Project in a nutshell:

• Consortium: AUCTUS@Inria, GEPETTO@LAAS (CNRS)

• Funding: None

• Duration: 2021 - ongoing

LORIA-AUCTUS collaborations

Participants:

Pauline Maurice (Researcher CNRS), Jessica Colombel (Postdoc),
François Charpillet (Senior Researcher Inria, LARSEN@LORIA),
Jonathan Savin (Engineer,
INRS), Ahmed-Manaf Dahmani,
Raphael Bousigues, David Daney, Vincent Padois, Nasser Rezoug.

Project AUCTUS

33

We have established a close scientific relationship with Larsen at LORIA, in recent years, through
several collaborative projects. Our main objective is to explore various approaches to the analysis
of human movement, with a particular focus on two specific themes: the inverse optimal control in
collaboration with the LAAS (see 8.2.1) and the study of motor variability in collaboration with INRS and
Institut P’ (see 8.2.3). In 2023, we submitted an ANR project focusing specifically on the latter theme,
demonstrating our ongoing commitment to research and the development of new innovative perspectives
in this constantly evolving field.

Project in a nutshell:

• Consortium:AUCTUS@Inria, LARSEN@LORIA (Inria-CNRS), INRS, Institut P’.

• Funding: None

• Duration: 2020 - ongoing

National visits to the team

Participants: Caroline Pascal.

• Caroline Pascal

Status PhD student

Institution of origin ENSTA

Dates 20 November to 1st December November 2023

Context of the visit Experimental work on the calibration of serial robots for high accuracy applic-

ations

Talk Robotized measurements for geometric and acoustic characterization of unknown structures

video

Mobility program/type of mobility R4 mobilty program

10.5 Regional initiatives

Robsys – Robustness of Autonomous Systems

Participants:

Auctus as a whole .

Auctus is particularly involved in WP1 on Robustness of Control / Decision Systems and WP3 on
Robust Human/Machine Interaction. It is also involed in WP6 through the co-advising of a PhD thesis
with the Rhoban Team on robus legged locomotion. Finally, Auctus has been retained by the leader of
WP8 as a "subject team" for study of the emergnence of ethical questions in the research process in
Robotics.

ROBSYS specializes in autonomous decision-making systems, including IoT devices, autonomous
vehicles, and various robotic applications deployed in diverse environments. These systems, integral to
Industry 4.0, operate in open settings such as disaster sites, agricultural fields, and households, making
decisions based on approximate and partial information. Inherent errors in autonomy are acknowledged,
highlighting the importance of robustness. For these critical systems, robustness goes beyond design
and construction quality, requiring an understanding of the environment and its elements. Detection
and prediction, from immediate ground characteristics to ethical and legal considerations, are crucial for
adapting and planning actions. The complexity increases in the realm of artificial intelligence, where fault
tolerance and auditability become challenging, especially in human interactions. Real-world machine
learning experiences, rather than just simulations, are emphasized, posing limitations (frugal AI), yet
underscoring the central role of data.

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Inria Annual Report 2023

In this context, the goal is to study fundamental issues overing all the functions of autonomous
systems from different angles (formal methods, stochastic models, and model-based analysis) as well as
to propose the design of experimentation prototypes and representative set-ups: Agricultural Robots,
legged robots usable in exploration context including agriculture, swarms of autonomous systems, in
particular for data collection (ground / air / infrastructures).

Beyond these technical aspects, ROBSYS also aims at studying the ethical issues brought by the
paradigm of autonomous systems as the concept of autonomy also questions the legal aspect in a deep
and no less essential way.

Project in a nutshell:

• Consortium: LABRI, IMS, IMB, Centre Inria de l’université de Bordeaux (AUCTUS@Inria, MNEMO-

SYNE@Inria), ONERA, I2M, IRDAP, IRGO

• Funding: Université de Bordeaux, Réseaux de Recherche Impulsion

• Duration: 2022 - 2025

Miels

Participants:

Erwann Landais, Nasser Rezzoug, Vincent Padois, David Daney.

The main objective of the MIELS project is to develop innovative strategies to characterize and develop
neoteric, non-toxic solvents through strategies that will enable to grasp the enormous quantity of required
experimental tests all in insuring an absolute safety of the manipulator. For this purpose, we intend to
work on two complementary routes, the development of solvent characterization methodologies and
the integration of a cobotic approach in solvent handling and evaluation, with the ambition of merging
these developments at the end of the project in order to draw as much synergy as possible. This project is
built around teams with complementary competencies to achieve these objectives. UMR LOF and Solvay
LOF have great experience acquired over several years of research the fields of solvent evaluation and
robotics, whereas Auctus INRIA team has a strong expertise in collaborative robotics. By combining our
competencies and expertise, the Miels project aims to merge all these fields in order to expand 1) the
fundamental study of solvents and their characterization techniques including theoretical techniques, in
particular for green solvents and 2) the development of the use of cobotics, in collaboration with Auctus
INRIA team, for increasing the efficacy and safety of laboratory workers in industry, in particular those
working on characterization of solvents.

Project in a nutshell:

• Consortium: AUCTUS@Inria, Solvay, LOF

• Funding: Région Nouvelle Aquitaine, Solvay

• Duration: 2020 - 2024

AAPR Perception-HRI

Participants: Cécile Scotto (Interactions@CeRCA), Louis Garcia, Margot Vulliez.

This regional project completes the ASAP-HRC ANR objectives with additional cognitive studies to
improve the exchange of perceptive information during Human-Robot interactions. Such an exchange of
information between the agents is required to communicate and coordinate together. We particularly
focus on visual and haptic feedbacks, related to the task, the context, or the robot assistance, and given
through a teleoperation device to perform an industrial task. Only a fine analysis and modeling of the
human multisensory perception and integration processes can provide practical guidelines to determine
the optimal mixture of feedbacks to implement in the human-robot interface. The project therefore

Project AUCTUS

35

aims at developing personalized mathematical models of the perceptive and sensorimotor integration of
visuo-haptic informations, in interaction scenarios with a robot.

Project in a nutshell:

• Consortium: AUCTUS@Inria (coordinator - Margot Vulliez), Interactions@CeRCA (CNRS, coordin-

ator - Cécile Scotto), RoBioSS@Pprime (CNRS)

• Funding: Région Nouvelle Aquitaine

• Duration: 2022 - 2025

Auctus@La-Coupole

Participants: Marjorie Paillet, Romain Pacanowski (Manao), Lucas Joseph (SED),

Vincent Padois.

La Coupole is a research projet led by Romain Pacanowski (Manano) aiming at providing a robotized
set-up for the digitalization of the visual appearance of historical artefacts. Given the expertise of the
Auctus team in robotics, an on-going informal collaboration between the two teams exists since 2022.
The adressed topics range from: control software architecture, motion planning, hardware adaptation
and design, robot calibration,...

Project in a nutshell:

• Consortium: AUCTUS@Inria, MANAO@Inria

• Funding: None

• Duration: 2022 - ongoing

R4 – Regional Network on Robotics Research

Participants:

Auctus as a whole .

R4 is a regional robotics network involving 12 research entities in the region of Nouvelle-Aquitaine,
France. The objective of the network is to boost research activities, mainly through a weekly working
group.

Project in a nutshell:

• Consortium: CRONE (IMS - University of Bordeaux / Bordeaux INP / CNRS), RHOBAN@LaBRI

(UB,Bordeaux INP,CNRS), PROGRESS@LaBRI (UB,Bordeaux INP,CNRS), AUCTUS@Inria, FLOWERS@Inria,
MNEMOSYNE@Inria, ESTIA-Recherche (ESTIA Bidart), LIUPPA (University of Pau and Pays de
L’Adour), REMIX (XLIM - University of Limoges), ROBIOSS (Institut PPRIME - University of Poitiers),
L3i (University of La Rochelle), I2M (ENSAM), ONERA

• Funding: Région Nouvelle-Aquitaine

• Duration: 2020 - ongoing

11 Dissemination

11.1 Promoting scientific activities

11.1.1 Scientific events: organisation

General chair, scientific chair

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Inria Annual Report 2023

• Nasser Rezzoug Scientific chair of the 48th congress of the French speaking Society of Biomechanics,

Grenoble, 25-27 october 2023.

• Vincent Padois Local chair the 2023 Journées Nationales de la Robotique Humanoïde, Bordeaux,

5th-7th July 2023

Member of the organizing committees

• David Daney, Benjamin Camblor and Jean-Marc Salotti organized the workshop Variability and

Adaptability in Human-Cobot Collaboration, Bordeaux (ENSC), December 2023.

• Lucas Joseph was part of the organization comitee of the ROSConfr, Bordeaux, July 4-5 2023.

• Antun Skuric was part of the organization comitee of the JNRH, Bordeaux, July 5-7 2023.

11.1.2 Scientific events: selection

Member of the conference program committees

• Lucas Joseph was part of the scientific comitee of the ROSConfr, Bordeaux, July 4-5 2023.

Reviewer List of conferences for which Auctus members have review activities :

• Robotics: 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
IEEE International Conference on Robotics and Automation (ICRA), ACM/IEEE Human Robot
Interaction (HRI 2024)

• Biomechanics: 2023 IEEE International Conference of the Engineering in Medicine and Biology

Society (EMBS), 48th congress of the french speaking Society of Biomechanics

11.1.3 Journal

Member of the editorial boards

• Nasser Rezzoug Journal of Biomechanics as representative of the french speaking Society of Bio-

mechanics

• Vincent Padois Associate Editor at ICRA and IROS

Reviewer - reviewing activities List of journals for which Auctus members have review activities:

• Robotics: IEEE Robotics and Automation Letters, Mechanism and Machine Theory, IEEE Transac-
tions on Robotics, IEEE Transactions on Haptics, Journal of intelligent manufacturing, International
Journal of Social Robotics

• Biomechanics: Journal of Biomechanics, Sports Biomechanics, Medical Engineering and Physics

• Software: Journal of Open Source Software

• Space: Microgravity Science and Technology, Journal of Aerospace Information Systems, Acta

Astronautica, Journal of Space Safety Engineering, QEIOS

• Others: Frontiers Neurosciences,

Project AUCTUS

11.1.4 Invited talks

37

• Virgile Batto - “A computational approach for optimizing the design of biped robots”, at R4, Novem-

ber 2023.

• Alexis Boulay - "A haptic guidance generic approach", JJCR 2023 - Journée des Jeunes Chercheurs

en Robotique, Oct 2023, Moliets et Maâ, France.

• Benjmain Camblor - “Managing attention through projection in human-robot collaboration”. Work-
shop Variability and Adaptability in Human-Cobot Collaboration, Bordeaux (ENSC), December
2023.

• Benjmain Camblor - “Situation awareness and attention sharing in human-robot interaction”.

Presentation for Pacbot project, Grenoble (LIG) May 2023.

• Benjmain Camblor - “Guide to conducting an empirical study of human-robot interaction”. Auctus

seminar, Bordeaux, March 2023.

• David Daney - "Human Posture Analysis for Human-robot Interaction", Workshop IIT Delhi,

October 2023.

• David Daney - "Cobotics for laboratories", Digital Days at Solvay, November 2023.

• David Daney - "Industrial robotics, challenges, work in progress and needs", Workshop Best,

December, 2023.

• Elio Jabbour - "Haptic shared control in human-robot collaboration", JJCR 2023 - Journée des

Jeunes Chercheurs en Robotique, Oct 2023, Moliets et Maâ, France.

• Gautier Laisne - “Musculoskeletal model identification using force polytopes”, at Institut Pprime

(Poitiers), March 2023, Talence.

• Antun Skuric - “Unifying view of physical ability metrics for humans, robots and their collaboration”,

at R4, June 2023.

• Antun Skuric - “Unifying view of physical ability metrics for humans, robots and their collaboration”,

at Biomimetics lab at the MIT, May 2023.

• Antun Skuric - “Approximating robot reachable space using convex polytopes”, at JNRH, July 2023.

• Nicolas Torres - “Model Predictive Control for robots adapting their task space motion online”, at

R4, June 2023.

• Nicolas Torres - “High-frequency Model Predictive Control for Online task-space trajectory re-

planning”, at PosterDay Stellantis, September 2023.

• Margot Vulliez - “Task, Hardware, and control: challenges in legged-robot design”, at JNRH, Bor-

deaux, July 2023

• Vincent Padois - "One or two vague (and somewhat pessimistic) ideas for a last minute presenta-
tion on robot control to open a Sunday lunch discussion" at Robotics Bordeaux Open Workshop
(ROBOW), Rhoban, Université de Bordeaux, Gradignan, Feb 2023

• Vincent Padois - "Collaborative Robotics: Myths, Legends and Facts or a few small steps towards
human-robot collaboration" at French-Italian Workshop on Robotics 4.0 for factories of the future,
Cité des Sciences, Paris, Jun 2023

11.1.5 Leadership within the scientific community

• Nasser Rezzoug is vice-President of the french speaking Society of Biomechanics.

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Inria Annual Report 2023

11.1.6 Scientific expertise

David Daney was a reviewer for "Défis Clés" of the regional initiative "Robotique centrée sur l’humain" of
the Occitanie region.

The Auctus team is involved in the “Aquitaine robotics” cluster, which brings together robotics players
in Nouvelle-Aquitaine. David Daney and Jean-Marc Salotti respectively represent Inria and Ensc on the
board of directors. David Daney is a member of the executive board. David Daney and Jean-Marc Salotti
are respectively president and vice-president of the labelling committee which promotes all robotics
projects for the Nouvelle-Aquitaine region.

The Auctus team is involved in the European Digital Innovation Hub DIHNAMIC. Within this frame-
work, David Daney has carried out several industrial expertise missions, notably for "retour à la plage"
and "Safran Helicopter Engines".

11.1.7 Research administration

• Virgile Batto is Doctoral students’ representative at the EdSys doctoral school

• David Daney is the principal investigator of ANR Pacbot

• David Daney is a member of the executive board of R4, a regional robotics network involving 12

research entities in the region of Nouvelle-Aquitaine, France.

• Vincent Padois is since september 2022 head of the “Commission des Développements Technolo-

giques” for the Inria Bordeaux research center.

• Jean-Marc Salotti is in charge of international relations at ENSC

• Jean-Marc Salotti is member of the Commission des Emplois de Recherche de Inria Bordeaux Sud-
Ouest (CER-BSO). He reviewed several PhD, Post-doc and "délégation" Applications in preparation
of deliberations.

• Margot Vulliez is the principal investigator of the ANR ASAP-HRC and AAPR Perception-HRI

projects.

11.2 Teaching - Supervision - Juries

11.2.1 Teaching

• Licence: Virgile Batto, Robotics, 5h eqTD, L2, BUT GE2I, Toulouse, France.

• Master: Alexis Boulay, Projet Informatique Individuel, 6h éqTD, M1, Ensc.

• Master: Alexis Boulay, Interactions humaines-robots et architectures cognitives, 10.6h éqTD, M2,

Ensc.

• Master: Alexis Boulay, Introduction à ROS 21.75h éqTD, M2, Enseirb.

• Master: Benjamin Camblor, Fonction cognitives en situation et Handicap, 11.25 éqTD, M1 (S7),

Master de Sciences cognitives et Ergonomie, Université de Bordeaux, France.

• Licence : Benjamin Camblor, TER (supervision of projects), 10h éqTD, L3 (S6), Licence MIASHS,

Université de Bordeaux, France.

• Licence : Benjamin Camblor, Fonction exécutives, 10.50h éqTD, L2 (S4), Licence MIASHS, Uni-

versité de Bordeaux, France.

• Master: David Daney, Interactions Humains Robots, 6h eqTD, M2, Ecole Nationale Supérieure de

Cognitique / Bordeaux INP, France.

• Master: David Daney, Mathématiques pour la robotique, 30h eqTD, M2, Enseirb/Ensc, Bordeaux

INP, France.

Project AUCTUS

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• Master: David Daney, oral expression, 3h eqTD, M2, Enseirb/Ensc, Bordeaux INP, France.

• Master: Guillaume de Mathelin, IA & Robotics: Planning,10h, M2 , Enseirb/ENSC, Bordeaux INP,

France.

• Master: Sébastien Dignoire, Projets de Robotique Mobile et introduction ROS, 40h éqTD, M2,

Polytech Sorbonne Université, Paris, France.

• Master: Gautier Laisné, Bases de l’intelligence artificielle, 16h éqTD, M1, École Nationale Supérieure

de Cognitique.

• Master: Gautier Laisné, Projet de fin d’études, 9h éqTD, M2, École Nationale Supérieure de Cogni-

tique.

• Master: Lucas Joseph, ROS, 10h éq TD, CESI, Bordeaux, France.

• Licence: Nasser Rezzoug, Biomécanique, 60h éqTD, L2, Faculté des Sciences du Sport (FSS),

Université de Poitiers, France.

• Licence: Nasser Rezzoug, Biomécanique, 10.5h éqTD, L1, Faculté des Sciences du Sport (FSS),

Université de Poitiers, France.

• Licence: Nasser Rezzoug, Biomécanique de la déficience motrice et du vieilliessement, 23h éqTD,

L3, Faculté des Sciences du Sport (FSS), Université de Poitiers, France.

• Licence: Nasser Rezzoug, Aspects biomécaniques du handicap, 18h éqTD, L3, Faculté des Sciences

du Sport (FSS), Université de Poitiers, France.

• Master: Nasser Rezzoug, Modalités de prescription de l’activité physique, 18h éqTD, M1, FSS Master

APAS/IRHPM, Université de Poitiers, France.

• Master: Nasser Rezzoug, Analyse cinematique et dynamique du mouvement, 20h éqTD, M1, FSS

Master APAS/IRHPM, Université de Poitiers, France.

• Master: Nasser Rezzoug, Métrologie, 16h éqTD, M1, FSS Master APAS/IRHPM, Université de

Poitiers, France.

• Master: Nasser Rezzoug, Ergonomie du poste de travail, 23h éqTD, M1, FSS Master APAS/IRHPM/

et SFA Ingénierie biomécanique, Université de Poitiers, France.

• Diplome d’Etat de masseur kinesitherapeute : Nasser Rezzoug, Biomécanique, 21h éqTD, CHU et

Université de Poitiers, France.

• Master: Antun Skuric, Mathématiques et Informatique (Intermédiaire), 15h éq TD, M1, ENSAM

Bordeaux, Arts et Métiers ParisTech, France.

• Master: Antun Skuric, Mathématiques et Informatique (Avancé), 15h éq TD, M2, ENSAM Bordeaux,

Arts et Métiers ParisTech, France.

• Master: Jean-Marc Salotti, Bases de l’intelligence artificielle (ENSC 2A), 40h eqTD.

• Master: Jean-Marc Salotti, Apprentissage Automatique (ENSC 2A), 25h eqTD.

• Master: Jean-Marc Salotti, Interactions Humains Robots (ENSC 3A), 32h eqTD.

• Master: Jean-Marc Salotti, Facteurs Humains et Ingénierie Cognitique (ENSC 3A), 28h eqTD.

• Master: Jean-Marc Salotti, supervision of projects and internships (ENSC 1A, 2A, 3A)and jury for

oral presentations, 100h eqTD.

• Master: Vincent Padois, Literature review - What, Why and How?, 20h éqTD, M2, Enseirb/Ensc,

Bordeaux INP, France.

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Inria Annual Report 2023

• Master: Vincent Padois, Maintenance du futur - Cours introductif, 2h éqTD, M1, ENSPIMA, Bor-

deaux INP, France.

• Master: Vincent Padois, Maintenance du futur - Introduction à la Robotique, 10h éqTD, M2,

ENSPIMA, Bordeaux INP, France.

• Master: Vincent Padois, Introduction à la Robotique, 2h éqTD, M1, Université de Bordeaux, France.

11.2.2 School

• Alexis Boulay participated in the winter school Agimus project on robotics at Banyuls-sur-Mer,

December 2023.

• Elio Jabbour participated in the winter school Agimus project on robotics at Banyuls-sur-Mer,

December 2023.

11.2.3 Supervision

PhD

• PhD in progress: Benjamin Camblor, Situation Awareness in Collaborative Robotics, funding: ANR

Pacbot, January 2020 - Jean-Marc Salotti .

• PhD in progress: Raphaël Bousigues (Thèse ED SPI, Bordeaux / INRS-Inria), “Motor variability in
human-robot collaboration”, December 2020 – Pauline Maurice, Vincent Padois , David Daney and
Jonathan Savin.

• PhD in progress: Erwann Landais (MIELS project, Région NA), “Approche robotique pour la formu-

lation de nouveaux solvants”,Sept 2021 –, Vincent Padois and Nasser Rezzoug.

• PhD in progress: Gautier Laisné (Inria), "Musculoskeletal models and data driven learning for
personalized human force capacities evaluation", October 2021 -, Nasser Rezzoug and Jean-Marc
Salotti.

• PhD in progress: Alexis Boulay (Farm3, Cifre), "Assister l’humain par un transfert de compétences

au robot en agriculture verticale téléopérée", June 2022 -, David Daney and Margot Vulliez.

• PhD in progress: Virgile Batto (CNRS), "Intelligence artificielle pour la co-conception de nouveaux
robots dynamiques à pattes : une approche de conception multidisciplinaire et générique", October
2022 -, Nicolas Mansard (LAAS-CNRS), Thomas Flayols (LAAS-CNRS) and Margot Vulliez.

• PhD in progress: Elio Jabbour (Inria), "Shared-autonomy control for improving Human-Robot
collaborarion in haptic teleoperation", funding: ANR ASAP-HRC, October 2022-, Margot Vulliez ,
Jean-Pierre Gazeau (Pprime Institute CNRS) and Vincent Padois.

• PhD in progress: Ahmed-Manaf Dahmani (Inria), "Robust inverse optimal control for human
motion analysis", funding: Inria, December 2023-, David Daney, François Charpillet (Inria Nancy).

• PhD in progress: Marc Duclusaud (Université de Bordeaux, Rhoban), "Learning for walking hu-
manoid robots", funding: RobSys, September 2022, Olivier Ly (Université de Bordeaux), Grégoire
Passault (Université de Bordeaux), Vincent Padois.

PhD passed

• PhD passed: Pierre Laguillaumie (Université de Poitiers), “Pierre Laguillaumie “Methodology for
the implementation of a new generation of collaborative robots taking into account the safety and
the biomechanical comfort of the operator in a work situation”, November 2018 / September 2023,
Jean-Pierre Gazeau and Vincent Padois.

Project AUCTUS

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• PhD passed: Nicolas Torres (Thèse ED SPI, Bordeaux / CIFRE PSA), “Synthesis and dynamic
analysis of the shared workspace for safety in collaborative robotics”, April 2020 / October 2023,
Vincent Padois and David Daney.

• PhD passed: Antun Skuric (Thèse ED SPI, Bordeaux / Financement projet Lichie Airbus), “A
coupled view of the physical abilities of human-robot dyad for the online quantitative evaluation
of assistance needs”, July 2020 / November 2023, Vincent Padois and David Daney.

Master

• Master 2: Ahmed-Manaf Dahmani (Robotics), "Robust inverse optimal control for human motion

analysis", April-Sept 2023, David Daney, François Charpillet (Inria Nancy)

• Master 2: Pierre Garnault (Robotics), “Modélisation et mesure des capacités de forces du membres
supérieur à l’aide d’un modèle musculosquelettique”, February - Aug 2023, Gautier Laisné, Jean-
Marc Salotti, and Nasser Rezzoug

• Master 2: Victor Dhédin (Robotics), "Parametrisation of robotic actions by demonstration", 2023,

Julie Dumora (CEA), Olivier David (CEA), Vincent Padois

• Master 1: Axel Plantey–veux, (Sciences cognitives et Ergonomie) “cobotic and human-robot inter-

action”, April 2023 - May 2023, Jean-Marc Salotti and Benjamin Camblor

• Master 1: Claire Houziel (Mechatronics and Rehabilitation, Sorbonne Université), "Improving
workspace sharing in collaborative Robotics", May-Jun 2023, Vincent Padois, Antun Skuric, Mar-
got Vulliez, Lucas Joseph

11.2.4 Juries

PhD

• David Daney

– Maxime Selingue, Reviewer, "Amélioration de la précision de structures sérielles poly-articulées
par des méthodes d’apprentissage automatique économes en données", HESAM Université,
ENSAM Lille, Richard Béarée, Adel Olabi et Stéphane Thiery, 22/12/2023.

• Nasser Rezzoug

– Brenda Elizabeth Olivas Padilla, Reviewer, "Deep state-space modeling for explainable rep-
resentation, analysis, and forecasting of professional human body dynamics in dexterity
understanding and computational ergonomics", Ecole des Mines de Paris, Université PSL,
19/03/2023.

– Théo Rouvier, Reviewer, "Approche biomécanique pour quantifier l’accessibilité en fauteuil

roulant manuel", ENSAM Paris, HESAM Université, 30/06/2023.

– Nicolas de l’Escalopier, Reviewer, "Évaluation par InertialoLocographie de l’impact de la
chirurgie du Pied Varus Équin Spastique sur la démarche des patients hémiplégiques après
Accident Vasculaire Cérébral", Centre Borelli, Université Paris Cité, 8/12/2023.

– Ajer Srihi, Examiner, "Stratégies de Stabilité en Position Assise chez les Personnes Vivant
avec une Lésion de la Moelle Épinière : de l’estimation utilisant des modèles descripteurs
quasi-LPV à la validation expérimentale", LAMIH (CNRS), Université Polytechnique des Hauts
de France, 21/12/2023.

– François Loisel, Reviewer, "Analyse cinématique et biomécanique de la main et du poignet par
modélisation personnalisée. Effet de lésions et d’instrumentations", ENSAM Paris, HESAM
Université, 22/12/2023.

• Margot Vulliez

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Inria Annual Report 2023

– Fanny Risbourg, Examiner, "Contributions à la commande prédictive pour la marche des

quadrupèdes sur terrain 3D", LAAS CNRS, Université de Toulouse, 31/01/2023.

• Vincent Padois

– Effie Segas, Reviewer, "Contrôle biomimétique de prothèses à partir des mouvements résiduels

et d’informations contextuelles", INCIA, Université de Bordeaux / CNRS, 24/03/2023

– Amit Parag, Reviewer, "A Supervised Formulation of Reinforcement Learning: toward Super-

linear Convergence Properties", LAAS CNRS, Université de Toulouse, 20/04/2023

– Mago Jesus, Reviewer, "Mechanical Design and Control of a Robotic Holder for Minimally

Invasive Surgery", ISIR CNRS/Inserm, Sorbonne Université, 15/05/2023

– Morgan Langard, Examiner, "Robot humanoïde bioinspiré - Conception et expérimentation",

LARIS, Université d’Angers, 18/12/2023

– Étienne Ménager, Reviewer, "Exploring state descriptions and soft robot simulations for

learning and control", Inria, Université de Lille, 21/12/2023

HDR Vincent Padois: Mourade Benoussaad, Reviewer, "Towards Physical Human Robot Collaboration :
Challenges and Perspectives", Université de Toulouse, 28/11/2023

Recruitment

• David Daney participated in recruitment jury MCF, IMT Altantique, 16/05/2023

• Nasser Rezzoug participated in recruitment jury MCF, Université de Poitiers, Institut Pprime,

16/05/2023

• Margot Vulliez participated in recruitment jury MCF, Université de Montpellier, LIRMM, 12/05/2023

Award

• David Daney participated as Jury member to the "Prix de thèse" 2022 of the "GDR Robotique".

• Nasser Rezzoug participated as Jury member to the senior researcher award "Prix Christian Oddou"

2023 of the french speaking international Society of Biomechanics.

11.3 Popularization

11.3.1 Articles and contents

• Gautier Laisné and Antun Skuric: Podcast speakers for “Désassemblons le numérique”, Inria de

l’Université de Bordeaux, June 2023, Talence.

• Vincent Padois : podcast serie "Une minute avec ..." link here, Centre Inria de l’Université de

Bordeaux, 2023, Talence.

• Lucas Joseph : podcast serie "Une minute avec ..." link here, Centre Inria de l’Université de Bordeaux,

2023, Talence.

11.3.2 Education

Un scientifique une classe – Chiche ! Seminars to raise general awareness of science and research careers
for secondary students

• Alexis Boulay, Lycée Maryse Condé, Sarcelles, December 2023

• Vincent Padois, Lycée Stendhal, Aiguillon (47), December 2023

• Vincent Padois, Fête de la Science, Inria Talence, October 2023

Project AUCTUS

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Classe transplantée Robot - CapScience Presentation of robotic research to primary school students

• Margot Vulliez, CapScience, Côté Sciences Air&Espace, Mérignac, April 2023.

• David Daney, CapScience, Côté Sciences Air&Espace, Mérignac, May 2023.

• Lucas Joseph, CapScience, Côté Sciences, Floirac October 2023.

• Margot Vulliez, CapScience, Côté Sciences Floirac, October 2023.

• Vincent Padois, Inria, École Jean Jaurès de Villenave d’Ornon, March 2023.

11.3.3 Event

• Alexis Boulay, Elio Jabbour, Lucas Joseph, Vincent Padois, “Fête de la science !”, Running a stand

demonstrating collaborative robotics algorithms, October 2023.

• Vincent Padois, “Fête de la science ! Le Bureau des Enquêtes”, October 2023.

• Nasser Rezzoug: 2023 french "National Biomechanics Day" event at the "Espace Mendès France"
(Poitiers), 5 april 2023. Various workshops were offered to college students and the general public
to present biomechanics. Evening seminars on biomechanics were offered to the general public.
Attendance: 80 people

• Alexis Boulay, Elio Jabbour, Lucas Joseph, Benjamin Camblor, Gautier Laisné, Claire Houziel,
Margot Vulliez, Vincent Padois, David Daney participated in the RoboCup that took place from
July 4th to July 10th, 2023. We organized several scientific events (JNRH, RosConfr), participated in
round-table discussions and conducted a public demonstration showcasing our scientific results.

11.3.4 Interventions

• David Daney, Gautier Laisné, Antun Skuric - “Unithé ou Café”, Inria de l’Université de Bordeaux,

April, Talence, 2023.

• Lucas Joseph - “Midi de la bidouille. Hugo”. INRIA, Novembre, Bordeaux, 2023.

• Margot Vulliez - invited to a public round-table at Robocup’23, and "Robots and Science-Fiction"

by Hypermondes, Bordeaux, July 2023.

12 Scientific production

12.1 Major publications

[1] N. Benhabib, V. Padois and D. Daney. ‘Securing Industrial Operators with Collaborative Robots:
Simulation and Experimental Validation for a Carpentry task’. In: ICRA 2020 - IEEE International
Conference on Robotics and Automation. Paris, France, 31st May 2020. DOI: 10.1109/ICRA40945
.2020.9197161. URL: https://hal.inria.fr/hal-02418739.

[2] B. Camblor, N. Benhabib, D. Daney, V. Padois and J.-M. Salotti. Task-Consistent Signaling Motions
for Improved Understanding in Human-Robot Interaction and Workspace Sharing. 6th Jan. 2022.
URL: https://hal.inria.fr/hal-03513888.

[3] P. Maurice, V. Padois, Y. Measson and P. Bidaud. ‘Human-oriented design of collaborative robots’.

In: International Journal of Industrial Ergonomics 57 (2017), pp. 88–102.

[4]

J. Savin, C. Gaudez, M. A. A. Gilles, V. Padois and P. Bidaud. ‘Evidence of movement variability
patterns during a repetitive pointing task until exhaustion’. In: Applied Ergonomics 96 (2021),
p. 103464. DOI: 10.1016/j.apergo.2021.103464. URL: https://hal.archives-ouvertes.f
r/hal-03280696.

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Inria Annual Report 2023

[5] A. Skuric, V. Padois and D. Daney. ‘Pycapacity: a real-time task-space capacity calculation package
for robotics and biomechanics’. In: Journal of Open Source Software 8.89 (12th Sept. 2023), p. 5670.
DOI: 10.21105/joss.05670. URL: https://inria.hal.science/hal-04316801.

[6] A. Skuric, V. Padois, N. Rezzoug and D. Daney. ‘On-line feasible wrench polytope evaluation
based on human musculoskeletal models: an iterative convex hull method’. In: IEEE Robotics and
Automation Letters (2022). DOI: 10.1109/LRA.2022.3155374. URL: https://hal.inria.fr/ha
l-03369576.

12.2 Publications of the year

International journals

[7] V. Bonnet, J. Mirabel, D. Daney, F. Lamiraux, M. Gautier and O. Stasse. ‘Practical whole-body elasto-
geometric calibration of a humanoid robot: Application to the TALOS robot’. In: Robotics and
Autonomous Systems 164 (June 2023), p. 104365. DOI: 10.1016/j.robot.2023.104365. URL:
https://hal.science/hal-04222944.

[8] V. Fortineau, I. A. Siegler, M. Makarov and P. Rodriguez-Ayerbe. ‘Human arm endpoint-impedance

in rhythmic human-robot interaction exhibits cyclic variations’. In: PLoS ONE 18.12 (2023), e0295640.
DOI: 10.1371/journal.pone.0295640. URL: https://hal.science/hal-04346387.

[9] G. Laisné, J.-M. Salotti and N. Rezzoug. ‘Genetic algorithms for force polytopes prediction’. In:
Computer Methods in Biomechanics and Biomedical Engineering 26.sup1 (24th Oct. 2023), pp. 218–
220. DOI: 10.1080/10255842.2023.2246304. URL: https://hal.science/hal-04396514.

[10]

J. Savin, D. Haering, N. Rezzoug and C. Pontonnier. ‘Simulation of maximum isometric and isokin-
etic elbow actuation torques based on zonotopes’. In: Computer Methods in Biomechanics and
Biomedical Engineering (2023), pp. 1–2. URL: https://inria.hal.science/hal-04140099.

[11] A. Skuric, V. Padois and D. Daney. ‘Pycapacity: a real-time task-space capacity calculation package
for robotics and biomechanics’. In: Journal of Open Source Software 8.89 (12th Sept. 2023), p. 5670.
DOI: 10.21105/joss.05670. URL: https://inria.hal.science/hal-04316801.

[12] A. Skuric, N. Rezzoug, D. Daney and V. Padois. ‘Dynamics aware Cartesian wrench polytope es-
timation based on human musculoskeletal models’. In: Computer Methods in Biomechanics and
Biomedical Engineering 26.sup1 (2023), S210–S212. DOI: 10.1080/10255842.2023.2246304.
URL: https://inria.hal.science/hal-04190087.

Invited conferences

[13] M. Desvergnes, N. Louveton, C. Scotto Di Cesare, K. Belhassein, M. Vulliez, P. Laguillaumie, C.
Préault, J. Pylouster, J.-P. Gazeau and L. Le Bigot. ‘Développement d’un scénario de maintenance
industriel, écologique et reproductible pour l’évaluation ergonomique des interfaces humain-
machine et de la charge mentale’. In: ERGO’IA 2023, October 10–13, 2023, Bidart, France. ERGO’IA
2023 - "L’avenir de l’humain dans les systèmes sociotechniques du futur". Biarritz, France, 2023.
URL: https://hal.science/hal-04405063.

International peer-reviewed conferences

[14] V. Batto, T. Flayols, N. Mansard and M. Vulliez. ‘Comparative metrics of advanced serial/parallel
biped design and characterization of the main contemporary architectures’. In: IEEE-RAS Interna-
tional Conference on Humanoid Robots 2023. Austin (Texas), United States, 12th Dec. 2023. URL:
https://hal.science/hal-04191553.

[15]

J. Colombel, D. Daney and F. Charpillet. ‘Holistic view of Inverse Optimal Control by introducing
projections on singularity curves’. In: IEEE International Conference on Robotics and Automation
(ICRA). 2023 IEEE International Conference on Robotics and Automation (ICRA). London, United
Kingdom: IEEE, 29th May 2023, pp. 12240–12246. DOI: 10.1109/ICRA48891.2023.10161163.
URL: https://hal.science/hal-03926294.

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[16] T. Faure, H. Decroux and J.-M. Salotti. ‘Adaptive Task Sharing in Collaboarative Robotics’. In:
Proceedings of the ICRA23 workshop: Cognitive Modeling in Robot Learning for Human Robot-
Interactions. ICRA23 - Workshop: Cognitive Modeling in Robot Learning for Human Robot-Interactions.
Londres, United Kingdom, 2nd June 2023, https://sites.google.com/view/cognitive-mod
eling-icra2023\bibrangedashws/contributions. URL: https://hal.science/hal-0413
3473.

[17] G. Laisné, J.-M. Salotti and N. Rezzoug. ‘Derivative-Free Optimization Approaches for Force Poly-
topes Prediction’. In: ESANN 2023 - European Symposium on Artificial Neural Networks, Computa-
tional Intelligence and Machine Learning. Bruges, Belgium, 2023, pp. 339–344. DOI: 10.14428/es
ann/2023.ES2023-122. URL: https://hal.science/hal-04330766.

[18]

[19]

J.-M. Salotti. ‘Long term shelters to avoid humanity extinction’. In: IAA Website. PDC 2023 - 8th IAA
Planetary Defense Conference. Vienna, Austria, Apr. 2023. URL: https://hal.science/hal-044
02965.

J.-M. Salotti. ‘Surface Energy Production Issues for the Refueling of Starships’. In: Proceedings of
the 74th IAC - IAF Website. IAC 2023 - 74th International Astronautical Congress. Baku, Azerbaijan,
Oct. 2023. URL: https://hal.science/hal-04402950.

National peer-reviewed Conferences

[20] M. Desvergnes, N. Louveton, C. S. Di Cesare, K. Belhassein, M. Vulliez, P. Laguillaumie, C. Préault, J.
Pylouster, J.-P. Gazeau and L. Le Bigot. ‘Définition et test d’un scénario de maintenance industrielle,
écologique et reproductible pour l’évaluation ergonomique des interfaces humain-machine et
de la charge mentale: Définition et évaluation d’un scénario de maintenance’. In: Ergo’IA 2023.
Biarritz, France, 10th Oct. 2023. URL: https://hal.science/hal-04291698.

Doctoral dissertations and habilitation theses

[21] P. Laguillaumie. ‘Software development for reactive multi-axis control: from low-level control to
connected digital twin’. Université de Poitiers - Faculté des Sciences Fondamentales et Appliquées,
7th Sept. 2023. URL: https://theses.hal.science/tel-04409449.

[22] A. Skuric. ‘A coupled view of the physical abilities of human-robot dyad for the online quantitative
evaluation of assistance needs’. University of Bordeaux; Inria, 6th Nov. 2023. URL: https://inria
.hal.science/tel-04396638.

[23] N. Torres Alberto. ‘Predictive Control of Collaborative Robots in Dynamic Contexts’. Universite

Bordeaux, 23rd Oct. 2023. URL: https://inria.hal.science/tel-04410378.

Reports & preprints

[24] B. Camblor, D. Daney, L. Joseph and J.-M. Salotti. Attention Sharing Handling Through Projection
Capability Within Human-Robot Collaboration. 17th Jan. 2024. URL: https://inria.hal.scien
ce/hal-04399124.

[25] V. Fortineau, V. Padois and D. Daney. Prediction of pose errors implied by external forces applied on
robots: towards a metric for the control of collaborative robots. 15th Sept. 2023. URL: https://inri
a.hal.science/hal-04410256.

[26] C. A. Rey Arias, W. Weekers, M. Morganti, V. Padois and A. Saccon. Refined Post-Impact Velocity
Prediction for Torque-Controlled Flexible-Joint Robots. 2023. URL: https://hal.science/hal-04
148817.

[27] N. Rezzoug, A. Skuric, V. Padois and D. Daney. Simulation Study of the Upper-limb Wrench Feasible
Set with Glenohumeral Joint Constraints. 2023. DOI: 10.48550/arXiv.2309.07487. URL: https:
//inria.hal.science/hal-04274526.

[28] N. Torres Alberto, A. Skuric, L. Joseph, V. Padois and D. Daney. Model Predictive Control for robots
adapting their task space motion online. 19th Apr. 2023. URL: https://inria.hal.science/hal
-04073876.

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Other scientific publications

[29] A. Boulay, D. Daney, M. Vulliez, R. Schmitt and A. Bonastre. ‘A haptic guidance generic approach’.
In: JJCR 2023 - Journée des Jeunes Chercheurs en Robotique. Moliets-et-Maâ, France, 15th Oct.
2023. URL: https://inria.hal.science/hal-04334395.

12.3 Cited publications

[30]

J. Bernon, E. Escriva and J. M. Schweitzer. Agir sur la prévention durable des TMS. Anact, 2011.

[31] F. Bunlon, J.-P. Gazeau, F. Colloud, P. J. Marshall and C. A. Bouquet. ‘Joint action with a virtual

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<scratchpad>
- Main topic: Research Centre AUCTUS at Inria
- Key points:
  - Focus on design of collaborative robots for humans
  - Emphasis on human-robot interaction, ergonomics, and safety
  - Research program includes analysis and modeling of human behavior, operator/robot coupling, and control design
  - Application domains include Factory 4.0, social and environmental responsibility, and new software platforms
  - Partnerships and cooperations with industry, academia, and research institutions
- Structure: The document is organized into sections on activity report, research program, application domains, new software platforms, partnerships and cooperations, and new results
- Potential artifacts to ignore: web-related elements, such as links, HTML tags, and other web-related elements
</scratchpad>

<final_summary>
The AUCTUS research centre at Inria focuses on designing collaborative robots that can work effectively with humans. The centre's research program includes analysis and modeling of human behavior, operator/robot coupling, and control design, with an emphasis on ergonomics and safety. The centre has partnerships with industry, academia, and research institutions, and has developed new software platforms and tools for collaborative robotics. The centre's work has applications in Factory 4.0, social and environmental responsibility, and other domains. Overall, the AUCTUS centre aims to improve human-robot interaction and collaboration, and to develop robots that can work safely and effectively with humans.
The AUCTUS research centre at Inria focuses on designing collaborative robots that can work effectively with humans. The centre's research program includes analysis and modeling of human behavior, operator/robot coupling, and control design, with an emphasis on ergonomics and safety. The centre has partnerships with industry, academia, and research institutions, and has developed new software platforms and tools for collaborative robotics. The centre's work has applications in Factory 4.0, social and environmental responsibility, and other domains. Overall, the AUCTUS centre aims to improve human-robot interaction and collaboration, and to develop robots that can work safely and effectively with humans.