SWAP: Test-Time Steerable Humanoid Whole-Body Collision Avoidance

Key points

• Humanoid robots operating in human-centric environments must coordinate the entire body to traverse tight, cluttered spaces while maintaining balance.1
• A high-level, perception-conditioned diffusion policy generates multimodal, collision-aware motion proposals, while a low-level whole-body RL controller tracks these proposals and maintains dynamic balance.1
• Experiments in simulation and on a real Unitree G1 humanoid show reliable avoidance with static and dynamic obstacles.1
• Together, these results support a practical solution to humanoid whole-body collision avoidance with test-time steerability.1

Sources (1)

• [1]SWAP: Test-Time Steerable Humanoid Whole-Body Collision Avoidance
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 19, 03:00 AM

  To address these challenges, we propose SWAP (Steerable Whole-body Avoidance Policy), a hierarchical framework that separates collision-aware decision making from stabilization.

  Humanoid robots operating in human-centric environments must coordinate the entire body to traverse tight, cluttered spaces while maintaining balance.

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