Professor in robotics and bioinspired control

patrick.henaff@enib.fr

Lab-STICC UMR CNRS 6285, École Nationale d’Ingénieur de Brest,

FRANCE

Patrick Hénaff is Professor since September 2013. Patrick Hénaff obtained a MSc in robotics from the Université Pierre et Marie Curie (France) in 1989 and a PhD in robotics in 1994 from the Robotic laboratory of Paris, Université Pierre et Marie Curie. From 1997 to 2013, he was a lecturer at the Technical Institute of the University of Cergy-Pontoise. From 1997 to 2009, he worked as a researcher at the LISV (Systems Engineering Laboratory at the University of Versailles) and from 2009 to August 2013, he was a researcher at the ETIS laboratory at the University of Cergy-Pontoise, CNRS UMR 8051. He worked as a Professor at the Ecole des Mines de Nancy of the University of Lorraine since September 2013 and in the LORIA laboratory (CNRS UMR 7503), Neurorhythms team. He was head of the Complex Systems, Artificial Intelligence and Robotics department at LORIA from 2015 to 2022 and head of the Computer Science department at Mines Nancy from 2018 to 2023. Since October 2023, he is Professor at the École Nationale d’Ingénieur de Brest and do his research at the Lab-STICC Laboratory (UMR CNRS 6285 ) in the Interaction department.

His research focuses on bio-inspired control in robotics. They aim to gain a better understanding of the learning mechanisms involved in motor coordination in humans, in order to model them and integrate them into humanoid robot controllers so as to give the latter movement learning capabilities. In particular, it is developing computational models of adaptive neural networks dedicated to controlling the rhythmic movements of humanoid robots.

Keynote title: Adaptive central pattern generators to control human/robot interactions

Abstract: The presentation will concern the use of bio-inspired robot controllers based on the functioning of specific biological sensori-motor loops that control biological systems. These loops are based on specific neural network structures, called central pattern generators (CPG) that are implied in the genesis and learning of adaptive rhythmic movements. Therefore, it is interesting to better understanding and modeling these structures to have humanoid robots able to learn rhythmic movements for locomotion or interacting with humans.

After a brief introduction on biological central pattern generators and the rhythmic movements, we will introduce the concept of synchronization a principle that underlies the rhythmic interaction between humans and the dynamic oscillators. Different models of central pattern generators based on dynamic oscillators will be introduced. The second part of the presentation will present several experiments of vision based Human-Robot motor coordination using adaptive central pattern generators. Other experiments of robot teleoperation for industrial rhythmic tasks will be introduced.

Several videos of simulations and experiments will illustrate the presentation. A conclusion and perspectives will conclude the talk.

Keywords: Humanoid robotics, Neural control, Central Pattern Generator (CPG), sensorimotor coordination, Human/robot interactions