Article

Jumper: Dynamic Jumping Control for a Crab Robot Based on Reference Motion and Residual Reinforcement Learning

Jumper uses a reference-guided residual reinforcement learning method to control dynamic jumping in a crab robot. The reference motion records only the nominal trajectory, and the policy learns only the corrections to the reference commands. In this method, the takeoff impulse determines the launch velocity, the ballistic trajectory determines the airborne phase, and the official policy is used to complete jumping and boundary tests.

Part of the event: Crab robot achieves dynamic jumping via reference-guided residual learning

This page provides a summary and source link only.