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CARO: Contact-Agnostic Residual Observation for Zero-Shot Robust Quadruped Locomotion

arXiv · AI, language, vision and robotics · article · Aug 25, 2026 · UTC

We propose CARO, a contact-agnostic residual observation framework for policy adaptation. CARO embeds a fixed-base Euler--Lagrange model into the reinforcement learning control loop and constructs a torque-level residual observation without requiring torque sensors, explicit contact estimation, or vision-based measurements of the floating-base position and linear velocity. A disturbance observer extracts a structured signal representing dynamics mismatch, while the policy learns to exploit this feedback for online adaptation. CARO is trained under the same terrain, command, and domain-randomiz

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