Research on gait control of humanoid robot based on DDPG algorithm

Humanoid robot has broad application prospects in services, entertainment, medical care, rescue, and other fields. Therefore, research on the stable walking problem of humanoid robot is particularly important. To solve this problem, this paper proposes a gait control method for humanoid robot according to reinforcement learning. We established a linkage model for humanoid robot and simplified it into a linear inverted pendulum model which was used for motion control of humanoid robot. Using DDPG network as an intelligent agent to train humanoid robot in gait control in a simulation environment. Due to the combination of DDPG and DQN structure, the stability and convergence of strategy network and critical network have been improved. The MATLAB simulation results show that under the action of the DDPG algorithm, the humanoid robot can walk smoothly along the predetermined trajectory through reinforcement learning.