引用本文:阮晓钢,周静,张晶晶,等.基于子目标搜索的机器人目标导向RRT路径规划算法[J].控制与决策,2020,35(10):2543-2548
【打印本页】   【HTML】   【下载PDF全文】   查看/发表评论  【EndNote】   【RefMan】   【BibTex】
←前一篇|后一篇→ 过刊浏览    高级检索
本文已被:浏览次   下载 本文二维码信息
码上扫一扫!
分享到: 微信 更多
基于子目标搜索的机器人目标导向RRT路径规划算法
阮晓钢,周静,张晶晶,朱晓庆
(1. 北京工业大学信息学部,北京100124;2. 北京工业大学计算智能与智能系统北京市重点实验室,北京100124)
摘要:
为解决移动机器人未知环境下的路径规划问题,提出基于子目标搜索的机器人目标导向RRT(rapidly- exploring random trees)路径规划算法.一方面,针对传统RRT算法固有的盲目搜索问题,引入目标导向函数,形成目标导向RRT路径规划算法,这一改进可减少冗余搜索,提高路径规划效率;另一方面,为了使机器人在首次探索未知环境时也能顺利抵达目标点,提出3种不同情况下的子目标搜索策略,包括无障碍环境下的直达策略、扫到边界点时的最短距离策略和扫不到边界点时的后退策略,这3种策略使机器人能够完成对未知环境的探索,而且可以克服易出现的局部极小点问题,使机器人具有逃离局部极小环境的能力.仿真实验结果验证了所提出算法的可行性和有效性.
关键词:  移动机器人  目标导向RRT  子目标搜索  未知环境导航  局部极小  路径规划算法
DOI:10.13195/j.kzyjc.2019.0043
分类号:TP273
基金项目:国家自然科学基金项目(61773027);北京市教育委员会科技计划重点项目(KZ201610005010);北京市自然科学基金项目(4202005).
Robot goal guide RRT path planning based on sub-target search
RUAN Xiao-gang, ZHOU Jing, ZHANG Jing-jing, ZHU Xiao-qing
(1. Faculty of Information Technology,Beijing University ofTechnology,Beijing100124,China;2. Beijing Key Laboratory of Computational Intelligence and Intelligent System,Beijing University of Technology,Beijing100124,China)
Abstract:
In order to solve the problem of path planning in the unknown environment of mobile robots, a path-planning algorithm of rapidly-exploring random trees(RRT) based on subtarget search is proposed. On the one hand, aiming at the blind search problem inherent in the traditional RRT algorithm, the objective guidance function is introduced to form a goal-directed RRT path planning algorithm, which can decrease redundant search, and improve the efficiency of path planning. On the other hand, in order to enable the robot to reach the target point successfully when it firstly explores the unknown environment, three sub-target search strategies under different circumstances are proposed, which include the direct strategy in the barrier-free environment, the shortest distance strategy when the boundary point is swept, and the backward strategy when the boundary point is not swept. They make the robot can complete exploration of the unknown environment, and, more importantly, can overcome the local minimum point of the problem. Simulation results verify the feasibility and effectiveness of the proposed algorithm.
Key words:  mobile robot  goal guide RRT  subtarget search  unknown environment navigation  local minimum  path planning algorithm

用微信扫一扫

用微信扫一扫