基于RRT*算法的移动机器人安全光滑路径生成
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中国石油大学(华东)海洋与空间信息学院 青岛 266400

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TP242

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国家自然科学基金面上项目(60271491)、自主创新科研计划项目(理工科)战略专项(22CX01004A)资助


Safe and smooth path generation of mobile robot based on RRT* algorithm
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School of Marine and Spatial Information, China University of Petroleum, Qingdao 266400, China

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    摘要:

    在多障碍物复杂工厂环境中,针对快速探索随机树算法(RRT*)生成的路径存在冗余点、贴近障碍物且存在锯齿状转折的问题,改进得到了安全光滑RRT*(SafeSmooth RRT*)路径规划算法。首先,引入目标偏置策略;其次,该算法利用融合目标点引力思想的新节点扩展方式以及改进的近邻点度量策略以减少树的盲目扩展,提高生长的目标性;随后,引入节点安全约束,将安全节点加入树中;改进路径简化方法,剔除冗余点的同时兼顾了安全性;最后通过B样条局部平滑来改善路径的平滑性。在MATLAB仿真实验中分别与标准RRT*算法、自适应目标偏向性RRT算法和改进RRT算法相比,在平均路径长度方面最大下降了7.1%,在平均有效节点数方面最大下降了64.1%,且所得路径始终与障碍物保持一定的安全距离,结果表明改进算法有效提升了路径的光滑性和安全性。

    Abstract:

    In complex factory environments with multiple obstacles, in order to solve the problem that the path generated by rapidlyexploring random tree star algorithm(RRT*) has redundant points, is close to the obstacle and has jagged turns, the path planning algorithm of SSRRT*[Safe-Smooth RRT*] is improved. Firstly, a target biasing strategy is introduced. Secondly, the algorithm utilizes a new node expansion approach that combines the concept of target point attraction and an improved nearest neighbor point metric to reduce the blind expansion of the tree and accelerate growth towards the target point; Node security constraints are then imposed to add the security nodes to the tree; Improved path simplification eliminates redundant points while taking into account security; Finally, the local smoothing of the B-spline is used to improve the smoothness of the path. By comparing with the standard RRT* algorithm, the adaptive target bias RRT algorithm, and improved RRT algorithm,the maximum decrease in average path length is 7.1%, the maximum decrease in average effective node number is 64.1%, and always keep a safe distance from obstacles. The results indicate that the improved algorithm effectively improves the smoothness and safety of the path.

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李文君,李忠伟,罗偲.基于RRT*算法的移动机器人安全光滑路径生成[J].电子测量技术,2024,47(2):51-60

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  • 在线发布日期: 2024-04-30
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