摘要
针对双向快速扩展随机树(RRT-Connect)算法的路径规划效率较低且采样具有随机性,提出了基于RRT-Connect的改进算法(DRRT-Connect)。该算法在起始点与目标点中间选取一个第三节点作为扩展点,使算法可以同时从起始点、目标点和第三节点生成四棵随机树;同时在改进算法中引入自适应步长调节函数,当探索无障碍空间时,算法使用步长调节函数增大扩展步长,从而提高随机树探索空间的速度;在RRT-Connect算法的基础上引入目标偏置策略,使DRRT-Connect在探索无障碍空间时可以朝目标点进行快速扩展,在探索障碍物空间时则调用随机采样函数,使算法可以快速摆脱障碍物,防止陷入局部最优。将DRRT-Connect算法分别与RRT、RRT-Connect、RRT^*算法进行仿真对比,结果表明DRRT-Connect在路径规划效率与迭代次数上均明显优于其他对比算法,其中相较于RRT-Connect算法,DRRT-Connect在路径规划速度上提高了50%,迭代次数上降低了32. 3%。
An improved RRT-Connect algorithm(DRRT-Connect), based on RRT-Connect was proposed to overcome the low efficiency and randomness in path planning of rapidly-exploring random tree connect (RRT-Connect) algorithm. Firstly, the algorithm selected a third node between the initial node and goal node as the extension node, so that the algorithm can generate four random trees from the initial node, goal node and the third node at the same time. In addition, the adaptive step-size adjustment function was introduced into the improved algorithm. The algorithm used the step-size adjustment function to increase the extended step size when exploring the free space. The function improved the exploring speed of random tree. Finally, a target-oriented strategy was introduced on the basis of RRT-Connect algorithm, which enabled the improved algorithm to expand rapidly towards the target node when exploring the free space, while the random sampling function was called when exploring the obstacle space, so that the algorithm could get rid of the obstacle quickly and avoid falling into local optimization. The simulation comparison of DRRT-Connect algorithm with RRT , RRT -Connect and RRT^* algorithms showed that the improved algorithm was significantly better than other algorithms in path planning efficiency and iteration times. The improved algorithm increased the path planning speed by 50% and reduces the iteration times by 32.3% compared with RRT-Connect algorithm.
作者
王坤
黄勃
曾国辉
李晓斌
WANG Kun;HUANG Bo;ZENG Guohui;LI Xiaobin(School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China;Center of Economic Crime Detection and Prevention and Control Technology Collaborative Innovation,Nanchang 330103, Jiangxi,China;College of Electrical and Electronic Engineering, Shanghai Institute of Technology , Shanghai 200235, China)
出处
《武汉大学学报（理学版）》
CAS
CSCD
北大核心
2019年第3期283-289,共7页
Journal of Wuhan University:Natural Science Edition
基金
国家自然科学基金(61603242)
上海工程技术大学机械电子工程学科建设项目(2018xk-A-03)
江西省经济犯罪侦查与防控技术协同创新中心开放课题(JXJZXTCX-030)
作者简介
王坤,男,硕士生,主要从事机器人控制、路径规划算法方面的研究。E-mail:M020217119@sues.edu.cn
