RL + Model-based Control: Using On-demand Optimal Control to Learn Versatile Legged Locomotion

no code implementations • 29 May 2023 • Dongho Kang, Jin Cheng, Miguel Zamora, Fatemeh Zargarbashi, Stelian Coros

These reference motions serve as targets for the RL policy to imitate, leading to the development of robust control policies that can be learned with reliability.

Reinforcement Learning (RL)