robotics
The Humanoid Kept Walking as Its Depth Sensor Faded
One locomotion policy denoised partial depth and blended body-state information instead of switching between perceptive and blind controllers.
Summary
One locomotion policy denoised partial depth and blended body-state information instead of switching between perceptive and blind controllers.
CAP trains a perceptive encoder to reconstruct clean depth from corrupted input while a second encoder supplies proprioceptive body state. Depth-noise curriculum and feature dropout expose the same policy to a continuum from clean vision to perception loss. In simulation it matched or exceeded perceptive baselines with useful depth and degraded more smoothly than a binary-switching baseline as input worsened. Controlled Unitree G1 tests and indoor-outdoor deployments showed locomotion under occlusion, sensor corruption and outdoor depth artifacts. The abstract does not establish universal terrain safety or quantify all physical trial outcomes.
Why it matters
One locomotion policy denoised partial depth and blended body-state information instead of switching between perceptive and blind controllers.
Limits and context
- The abstract does not establish universal terrain safety or quantify all physical trial outcomes.
Key claims
One locomotion policy denoised partial depth and blended body-state information instead of switching between perceptive and blind controllers.
Qualification: The abstract does not establish universal terrain safety or quantify all physical trial outcomes.
Evidence: source-2026-09-11-014
Sources
- arXiv preprint 2609.11553arXiv · primary research
Corrections
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