基于路径积分强化学习的爬行步态蛇形机器人路径跟踪

Renpeng Wang, W. Xi, Xian Guo, Yongchun Fang
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摘要

提出了一种具有正交关节的蛇形机器人采用履带步态跟踪路径的方法。考虑到蛇形机器人系统的冗余性,提出了一种新的路径积分强化学习(PI2)框架。首先利用履带步态的特点,将路径跟踪问题简化为求解其最优曲率序列;然后在求解过程中采用滚动优化算法,提高求解效率和实时性。在滚动优化中引入路径积分,提高求解质量。最后,我们通过仿真验证了该帧,其结果符合目标路径。
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Path Following for Snake Robot Using Crawler Gait Based on Path Integral Reinforcement Learning
This paper presents a method for snake robots with orthogonal joints to follow a path via crawler gait. Considering snake robot system’s redundancy, a novel path integral reinforcement learning (PI2) framework is applied to solve it. Taking advantage of crawler gait, the path following problem is first simplified to solve optimal curvature sequence for it. Then rolling optimization algorithm is adopted through the solving process to improve solution efficiency and real-time performance. Moreover, path integral is integrated into the rolling optimization to improve solution quality. Finally, we validate the frame by simulation, with results that follow the target path.
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