东北大学学报（自然科学版）

东北大学学报（自然科学版） ›› 2021, Vol. 42 ›› Issue (8): 1065-1071.DOI: 10.12068/j.issn.1005-3026.2021.08.001

• 信息与控制 •    下一篇

基于改进双向RRT*的移动机器人路径规划算法

王海芳， 张瑶， 朱亚锟， 陈晓波   

  1. (东北大学秦皇岛分校 控制工程学院， 河北 秦皇岛066004)
  • 修回日期:2020-12-21 接受日期:2020-12-21 发布日期:2021-09-02
  • 通讯作者: 王海芳
  • 作者简介:王海芳(1976-)， 男， 山西高平人， 东北大学副教授.
  • 基金资助:
    国家自然科学基金资助项目(61703079)； 秦皇岛市大学生科技创新创业专项基金资助项目(2018-79，121).

Mobile Robot Path Planning Based on Improved Bidirectional RRT*

WANG Hai-fang， ZHANG Yao， ZHU Ya-kun， CHEN Xiao-bo   

  1. School of Control Engineering， Northeastern University at Qinhuangdao， Qinhuangdao 066004， China.
  • Revised:2020-12-21 Accepted:2020-12-21 Published:2021-09-02
  • Contact: WANG Hai-fang
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摘要： 针对复杂环境下移动机器人的局部最优路径规划，提出一种基于目标偏置扩展和Cantmull-Rom样条插值的双向RRT*路径规划算法.双向RRT*算法同时创建两颗搜索树，交替进行相向搜索，同时以一定的概率进行随机点的目标偏置选择，以提高算法的整体收敛效率;再对当前节点重选父节点和重布线，以增强算法对环境的敏感程度.为确保路径安全可行，对环境中的障碍物进行膨胀处理，再对初始路径进行碰撞检测;修剪冗余节点，缩短可行路径长度，再利用Cantmull-Rom样条插值法平滑路径.在Matlab仿真平台和ROS机器人仿真平台分别进行2D和3D的对比实验，验证了改进双向RRT*算法的有效性和优越性.

关键词: 快速探索随机树;Cantmull-Rom样条插值;ROS机器人仿真平台;改进双向RRT*

Abstract: Aiming at local optimal path planning of mobile robots in complex environments， a bidirectional rapidly exploring random tree star(Bi-RRT*)path planning algorithm based on target offset expansion and Cantmull-Rom spline interpolation is proposed. In the Bi-RRT* algorithm， two search trees are created at the same time， and opposite searches are alternately performed with the target bias of random points selected at a certain probability， in order to improve the overall convergence efficiency of the algorithm. By reselecting the parent node of the current node and rewiring the nodes， the sensitivity to the environment of path planning is enhanced. To ensure the path safe and feasible， the obstacles in environment are expanded and collision detection is performed on the initial path. Redundant nodes are trimmed so that the feasible path length is shortened. Then， the path is smoothed by the Cantmull-Rom spline interpolation. The 2D and 3D comparative experiments were conducted for the improved Bi-RRT* algorithm based on Matlab and ROS robot simulation platform， respectively， and the experiment results verified the effectiveness and superiority of the improved Bi-RRT* algorithm.

Key words: rapidly exploring random tree; Cantmull-Rom spline interpolation; ROS robot simulation platform; improved Bi-RRT*

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