AI RESEARCH
KINESIS: Motion Imitation for Human Musculoskeletal Locomotion
arXiv CS.LG
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ArXi:2503.14637v3 Announce Type: replace-cross How do humans move? Advances in reinforcement learning (RL) have produced impressive results in capturing human motion using physics-based humanoid control. However, torque-controlled humanoids fail to model key aspects of human motor control such as biomechanical joint constraints & non-linear and overactuated musculotendon control. We present KINESIS, a model-free motion imitation framework that tackles these challenges. KINESIS is trained on 1.8 hours of locomotion data and achieves strong motion imitation performance on unseen trajectories.