Elliot Chane-Sane

Postdoctoral Researcher in Robot Learning

I am a postdoctoral researcher at LAAS-CNRS in the Gepetto team working on robot learning under the supervision of Nicolas Mansard. Previously, I completed my PhD in the Willow team of Inria Paris and École Normale Supérieure, advised by Ivan Laptev and Cordelia Schmid.

I am interested in deep learning, reinforcement learning (RL), and vision, toward building generalist robots that could go everywhere and perform every task. I have worked on goal-conditioned RL, agile legged locomotion, and visual imitation from large video datasets.

Prior to research, I received an engineering degree from École Polytechnique and a MASt (Part III) in Mathematical Statistics from the University of Cambridge.

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Research

Learning legged locomotion skills by watching thoushands of wild animal videos from the internet

End-to-end visual RL for agile legged robot parkour from depth pixels

A simple constrained RL method that efficiently scales to large numbers of constraints, greatly facilitating reward engineering

Zero-shot video demonstration to robot manipulation by watching thoushands of human videos

Leveraging compositionality in long-horizon reasoning to learn goal-reaching policies

Design and source code from Jon Barron's website.