What if we could generate complex movements for arbitrary robots with arms and legs interacting in a dynamic environment in real-time? Such a technology would certainly revolutionize the motion capabilities of robots and unlock a wide range of very concrete industrial and service applications: robots would be able to react in real-time to any change of the environment or unexpected disturbance during locomotion or manipulation tasks. However, the computation of complex movements for robots with arms and legs in multi-contact scenarios in unstructured environments is not realistically amenable to real-time with current computational capabilities and numerical algorithms.
The project Memmo aims to solve this problem by 1) relying on massive off-line caching of pre-computed optimal motions that are 2) recovered and adapted online to new situations with real-time tractable model predictive control and where 3) all available sensor modalities are exploited for feedback control going beyond the mere state of the robot for more robust behaviours.
We will show the current results we have been able to achieve on the humanoid robot TALOS.
Olivier Stasse is a CNRS Senior scientist in humanoid robotics at LAAS-CNRS, Toulouse France. His research interest is in fast decision making to generate motion for humanoid robotics. He managed the specifications and the contracting of the first humanoid robot of the TALOS series from PAL-ROBOTICS. He is co-directing the joint lab ROB4FAM with Airbus Toulouse, and is currently serving as an Associate Editor for the IEEE Transactions on Robotics. He received in 2000 a Ph.D. on Intelligent Systems from the University of Paris 6, and the French Habilitation to Supervise Research (HDR) in Robotics (2013) from the University of Toulouse III. From 2000 to 2003, he was assistant professor at the Univ. of Paris XIII. From 2003 to 2011, he was at the Joint French-Japanese Robotics Laboratory (JRL) between the CNRS and the AIST in Tsukuba. In 2011 he joined the Gepetto team at LAAS, and is leading the team since 2021.