SOURCE-LINKED INTELLIGENCE
CAP: Continuously Adaptive Perception-Blind Humanoid Locomotion via Learned Denoising
Humanoid locomotion across complex terrain demands forward-looking exteroception to anticipate obstacles, yet this signal is unreliable in real-world deployment, failing partially and intermittently. Existing perceptive policies often assume that depth observations remain clean and in-distribution, while recent attempts to unify perceptive and blind control typically route or switch between separate sub-policies, leaving recoverable information in partially corrupted depth unexploited. We instead propose CAP, a single-stage humanoid locomotion policy that recovers this signal with a perceptive
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-10T13:45:10.000Z
First collected: 2026-09-20T19:02:05.452Z. This is not the publication date.