Beyond Kinematic Tracking: Preserving Expressive Characteristics in Humanoid Whole-Body Control

Key points

• Our analysis shows that lower average positional tracking error does not guarantee better preservation of dynamic and postural motion characteristics.1
• To address this gap, we propose a residual learning framework with compensation objectives targeting amplitude, energy, body expansion, body lean, and pelvis height.1
• To concentrate compensation while limiting interference with the underlying tracking behavior, motion-aware gating allocates correction capacity according to body-part activity, preserving larger correction ranges in more active parts and restricting them elsewhere.1
• Simulation and physical experiments on the Unitree G1 across eight motion categories demonstrate superior preservation of dynamic and postural motion characteristics compared with the corresponding baselines.1

Sources (1)

• [1]Beyond Kinematic Tracking: Preserving Expressive Characteristics in Humanoid Whole-Body Control
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 14, 01:39 AM

  Whole-body control plays a crucial role in enabling humanoid robots to execute expressive motions.

  Our analysis shows that lower average positional tracking error does not guarantee better preservation of dynamic and postural motion characteristics.

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