SOURCE-LINKED INTELLIGENCE
Collision-Aware Humanoid Whole-Body Control under Imperfect Tracking Targets
Humanoid robots often execute motion commands through whole-body controllers (WBCs) that track targets while maintaining balance and stability. However, most WBCs are blind to scene geometry, which can lead to collisions from imperfect target motions that are geometrically unsafe due to perception, planning, or teleoperation errors. We propose RECAL, a Robot--Environment Cross-Attention Layer that wraps a blind WBC to trade off target tracking against collision avoidance using external scene geometry. RECAL supports collision-aware tracking of floating-base and end-effector commands, including
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-14T22:22:02.000Z
First collected: 2026-09-20T09:01:24.920Z. This is not the publication date.