Hongsheng Zeng

Reinforcement Learning With Evolutionary Trajectory Generator: A General Approach for Quadrupedal Locomotion

Recently reinforcement learning (RL) has emerged as a promising approach for quadrupedal locomotion, which can save the manual effort in conventional approaches such as designing skill-specific controllers. However, due to the complex nonlinear dynamics in quadrupedal robots and reward sparsity, it