Perception

Body Schema

A body schema is an agent's internal model of its own body, including link geometry, joint configuration, dynamics, and the sensory consequences of its motion, a concept imported from neuroscience where it explains phenomena like tool incorporation. In robotics it covers learned self-models: networks that predict the robot's occupancy for self-collision checking, calibrate kinematics from experience, and adapt online when the body changes through damage or grasped tools.

Why it matters for physical AI

Robots that learn and update their own body models can absorb calibration drift, hardware variation, and tool use without re-engineering, a capability cross-embodiment foundation policies implicitly require.