Research on Motion Planning of Hexapod Robot Based on DRL and Free Gait
To improve the passability and the motion performance of the hexapod robot in the unstructured environment,a multi-contact motion planning algorithm based on DRL and free gait planner is proposed.Firstly,the free gait planner obtains the reachable footholds under the target state and outputs the optimal gait sequence.The center of mass motion policy of the hexapod robot in the randomly generated plum blossom pile environment is obtained by using deep reinforcement learning training.To ensure the reachability between adjacent states of the robot in motion,the state transition feasibility model is used to judge the state transition feasibility.Finally,the foothold planning of the hexapod robot in the plum blossom pile environment with gullies of different widths is realized.Simulation and physical experiments show that the multi-contact motion planning algorithm can make the robot reach the target area quickly and smoothly from the starting point,and automatically adjust the gait pattern to deal with the randomly distributed plum blossom piles in different environments.
万方数据
维普
