Robotics - LAAS-CNRS

Department rob

Robotics

The robotics department is developing a multi-thematic field of research focusing on the development of perception, decision, movement generation and communication functions for robots, intended to be tested in real, uncontrolled environments. It is equipped with a very complete robotic platform.

head

Olivier Stasse

The department is structured into three research teams which work in synergy and whose areas of expertise are complementary.

The “Gepetto” team, specialist in the movement of anthropomorphic systems, has three research objects: the humanoid robot, the digital mannequin and Human. Its expertise is focused on the planning, generation and control of the movement of these unstable poly-articulated systems. It carries out interdisciplinary activity at the intersection of robotics, neuroscience and biomechanics with a particular interest in the design of artificial muscles.

The activity of the “Robotics, action and perception” (RAP) team, experts in signal processing, is centered on the “perception-action” link, with a focus on vision and hearing. Its areas of research are: detection, segmentation, identification and tracking of people and objects; perception and control in a dynamic environment and the development of integrated sensors. The challenges to be met are taking into account the variability of the environment and the constraints of embedding and real-time calculation. The team develops original solutions emphasizing probabilistic data fusion.

The “Robotics and its interactions” (RIS) team focuses its expertise on interactions with humans and the environment. Its activities cover systems architecture, physical control and interactions, temporal planning and reasoning, motion planning and learning. The methods and algorithms developed are exploited in three main areas: terrestrial and aerial robotics, with a strong focus on multi-robot cooperation and environment modeling, cognitive and interaction robotics and molecular movement.

These three teams maintain close collaboration with each other, as well as with other laboratory teams attached to different scientific departments. Their work is carried out within the framework of a large number of European projects (ESA, FP7, Horizon Europe, EraNet, etc.), national and regional, and direct industrial collaborations. The applications concern a wide range of fields: agriculture, transport, factory of the future, service robotics, home automation and ambient intelligence, virtual reality and animation, surveillance and civil security, planetary and space exploration, biochemistry, etc.

A large number of software developed by the department researchers are distributed in open access (GenoM3, GDHE, OpenPRS, Jafar, HPP, SoT, Pinocchio, etc.).

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RESEARCH AND APPLICATIONS

DISCIPLINARY FIELDS

COVERED IN OUR DEPARTMENT

DEPARTMENT TEAMS

The department is composed of 3 research teams: Robotique et Interactions (RIS), Robotique, Action, Perception (RAP) et GEPETTO.

gepetto

Nicolas Mansard

The research activity of the Gepetto team is focused on the analysis and generation of movement of anthropomorphic systems. Created in 2006, it quickly became one of the leading teams in humanoid robotics, unanimously recognized for its expertise in movement …

rap

Patrick Danes

The research conducted by the RAP team concerns the design, prototyping, implementation and evaluation of algorithms for: visual perception; sensor-based control and navigation; interactive mobile manipulation; multi-sensor data modeling and fusion.

ris

François Félix Ingrand

The "Robotics and InteractionS" team develops a research project on autonomous mobile machines that integrate perception, reasoning, learning, action and reaction capabilities. The challenge is on their capacity to act rationally in dynamic environments to achieve a large variety of …

Latest publications

2026

Journal articles

Pietro Noah Crestaz, Ludovic de Matteis, Elliot Chane-Sane, Nicolas Mansard, Andrea del Prete. TD-CD-MPPI: Temporal-Difference Constraint-Discounted Model Predictive Path Integral Control. IEEE Robotics and Automation Letters, 2026, 11 (1), pp.498-505. ⟨10.1109/LRA.2025.3632612⟩. ⟨hal-05213269v2⟩

Andrea Dal Prete, Zeynep Özge Orhan, Anastasia Bolotnikova, Marta Gandolla, Auke Ijspeert, et al.. Locomotion Mode Transitions: Tackling System- and User-Specific Variability in Lower-Limb Exoskeletons. IEEE/ASME Transactions on Mechatronics, In press, ⟨10.1109/tmech.2025.3628049⟩. ⟨hal-05410450⟩

Eliott Lumet, Mélanie C Rochoux, Thomas Jaravel, Simon Lacroix. Surrogate-based ensemble data assimilation for reducing uncertainty in large-eddy simulation of microscale pollutant dispersion. Building and Environment, 2026, 287, pp.113863. ⟨10.1016/j.buildenv.2025.113863⟩. ⟨hal-05420659⟩

2025

Journal articles

N. Poquerusse, A. Hays, A. Cortial, O. Vigié, M. Deves, et al.. Measurement of skidding to determine the optimum ergonomic configuration of the racing wheelchair. Multidisciplinary Biomechanics Journal, 2025, 49th congress of the Société de Biomécanique, ⟨10.46298/mbj.14556⟩. ⟨hal-04738045v2⟩

Zoé Pomarat, Jean-Charles Passieux, John-Eric Dufour, Bruno Watier. Machine learning techniques for estimating the individual three-dimensional ground reaction forces during rugby scrummaging. Journal of Biomechanics, 2025, 193, pp.113015. ⟨10.1016/j.jbiomech.2025.113015⟩. ⟨hal-05330563⟩

Z. Pomarat, Thibault Marsan, A. Faupin, Y. Landon, Bruno Watier. Wheelchair caster power losses due to rolling resistance on sports surfaces. Disability and Rehabilitation: Assistive Technology, 2025, 20 (4), pp.1176-1182. ⟨10.1080/17483107.2024.2406450⟩. ⟨hal-04725578⟩

Thibault Marsan, Mickael Barbat, Élodie Dancerel-Bourlon, Bruno Watier. Turning judges ranking into biomechanical parameters for cheerleading. Multidisciplinary Biomechanics Journal, 2025, 49th congress of the Société de Biomécanique, ⟨10.46298/mbj.14557⟩. ⟨hal-04738046v2⟩