Project Description

Controlling the dynamics of complex systems requires identifying and tuning more and more parameters, leading to increasing adaptation times for new tasks or new robots. In this project, we plan to make this process automatic and online to constantly improve the performance during the robot operation. Classical control techniques, together with statistical tools and machine learning will be exploited to this end.



Funded by

Title Authors Conference/Book Year bib pdf
Learning Bipedal Walking for Humanoids with Current Feedback R. Singh, Z. Xie, P. Gergondet, F. Kanehiro IEEE Access 2023
Mc-Mujoco: Simulating Articulated Robots with FSM Controllers in MuJoCo R. Singh, P. Gergondet, F. Kanehiro IEEE/SICE International Symposium on System Integration 2023
Learning Bipedal Walking on Planned Footsteps for Humanoid Robots R. Singh, M. Benallegue, M. Morisawa, R. Cisneros-Limón, F. Kanehiro IEEE-RAS International Conference on Humanoid Robots 2022