基于DRL和自由步态的六足机器人运动规划研究

Research on Motion Planning of Hexapod Robot Based on DRL and Free Gait

为提高六足机器人在非结构环境下的通过率和运动性能,提出一种基于DRL和自由步态规划器的多接触运动规划算法。自由步态规划器获取目标状态下可达落足点从而输出最优步态序列;利用DRL训练得到六足机器人在随机生成的梅花桩环境中的质心运动策略。为了保证机器人在运动过程中相邻状态之间的可达性,利用状态转移可行性模型对状态转移可行性进行判定,实现六足机器人在不同宽度沟壑梅花桩环境下的落脚点规划。仿真与样机实验表明:多接触运动规划算法能够让机器人快速平稳地从起点到达目标区域,并自动调整步态模式以应对不同环境下随机分布的梅花桩。

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.