5 papers
Direct Dynamic Retargeting for Humanoid Imitation Learning from Videos
Constant Roux, Ludovic De Matteïs, Armand Jordana +4
Imitation Learning from monocular video demonstrations provides a scalable approach for teaching complex skills to humanoid robots. However, translating human motion to humanoids r…
Latent Conditioned Loco-Manipulation Using Motion Priors
Maciej StÄpieÅ, Rafael Kourdis, Constant Roux +1
Although humanoid and quadruped robots provide a wide range of capabilities, current control methods, such as Deep Reinforcement Learning, focus mainly on single skills. This appro…
Constrained Reinforcement Learning for Unstable Point-Feet Bipedal Locomotion Applied to the Bolt Robot
Constant Roux, Elliot Chane-Sane, Ludovic De Matteïs +4
Bipedal locomotion is a key challenge in robotics, particularly for robots like Bolt, which have a point-foot design. This study explores the control of such underactuated robots u…
Reinforcement Learning from Wild Animal Videos
Elliot Chane-Sane, Constant Roux, Olivier Stasse +1
We propose to learn legged robot locomotion skills by watching thousands of wild animal videos from the internet, such as those featured in nature documentaries. Indeed, such video…
Whole-body MPC and sensitivity analysis of a real time foot step sequencer for a biped robot Bolt
Constant Roux, Côme Perrot, Olivier Stasse
This paper presents a novel controller for the bipedal robot Bolt. Our approach leverages a whole-body model predictive controller in conjunction with a footstep sequencer to achie…