Subequivariant Reinforcement Learning Framework for Coordinated Motion Control
Haoyu Wang,Xiaoyu Tan,Xihe Qiu,Chao Qu,Haoyu Wang,Xiaoyu Tan,Xihe Qiu,Chao Qu
Effective coordination is crucial for motion control with reinforcement learning, especially as the complexity of agents and their motions increases. However, many existing methods struggle to account for the intricate dependencies between joints. We introduce CoordiGraph, a novel architecture that leverages subequivariant principles from physics to enhance coordination of motion control with rein...
