Control
Inverse Dynamics
Inverse dynamics is the computation of the joint torques required to produce a specified motion, given joint positions, velocities, and accelerations along with the robot's mass and inertia parameters. The Recursive Newton-Euler Algorithm computes it efficiently for kinematic chains, and it underpins computed-torque control, feedforward compensation, and gravity compensation in torque-controlled robots.
Why it matters for physical AI
Feedforward torques from inverse dynamics let controllers track aggressive motions with low feedback gains, enabling the compliant yet precise behavior that dynamic legged and manipulation platforms depend on.
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