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Research on Asynchronous Upper-Body Task-Space Trajectory Tracking Strategies for Humanoid Robots

The paper proposes an asynchronous upper-body task-space trajectory tracking framework for humanoid robots, addressing the temporal asynchrony between sparse, low-frequency trajectories output by high-level planners and the high-frequency operation of whole-body controllers. The student policy is initialized through teacher-student distillation, conditioned on the fully cached future trajectory and an execution-time index, and trained with a sliding-window global reward to reduce frame drift; in the task post-training stage, an MPC module completes sparse references into floating-base and upper-body guidance.

Part of the event: Proposal of an asynchronous upper-body trajectory tracking framework for humanoid robots

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