Lijin Han

Pareto frontier-guided differentiated skill reinforcement learning for quadrupedal wheeled-legged robots

Wheeled-legged robots possess both extreme maneuverability and strong terrain adaptability, but there is an inherent physical contradiction between high-speed locomotion and disturbance-rejection robustness. Traditional end-to-end reinforcement learning (RL) methods typically rely on black-box trial and error, lacking...

A hierarchical multiscale reinforcement learning framework for energy management in hybrid electric vehicles considering powertrain response coordination