Control

Computed Torque Control

Computed torque control is a model-based control method that uses the robot's inverse dynamics to cancel nonlinear dynamics, applying feedback linearization so the closed-loop system behaves as a set of decoupled linear double integrators. Joint torques are computed from the mass matrix, Coriolis, and gravity terms evaluated along the desired trajectory, plus PD feedback on tracking error. Performance depends directly on the accuracy of the dynamic model.

Why it matters for physical AI

Model-based torque control provides the precise, high-bandwidth tracking layer beneath many learned systems, and its sensitivity to model error motivates learned residual dynamics and adaptive extensions.