Performing pirouettes, tennis strokes, or celebrating goals in a match with the naturalness of a human being is now possible for a robot. The BeyondMimic project presents a new robotic learning framework fed with human motion data to create natural physical behaviors.
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The robot can walk, run, and execute complex movements inspired by martial arts. After training it with about 2.5 hours of human motion data, researchers first validated their method in a simulation environment before conducting physical experiments on different terrains. The study was published today Wednesday in the journal Science Robotics.
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The flexibility of the learning model allows it to assimilate new skills without the need for specific training for each new task. BeyondMimic converts motion data into continuous representations and generates reproducible trajectories, without the need for dedicated learning for each gesture. Until now, most learning methods for robots required constant adjustments and produced unnatural movements.
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