基于切点搜索和约束b样条的路径规划算法

IF 5.2 2区 计算机科学 Q2 ROBOTICS
Ge Tai, Chaoyi Dong, Shuai Xiang, Tianyu Yuan, Haoda Yan, Qilai Wang, Xiaoyan Chen
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引用次数: 0

摘要

传统的切点搜索算法(TPS)作为一种适用于大尺度地图的路径规划算法,在存在大型矩形障碍物的情况下表现良好。然而,它有两个缺点:1。它要求障碍物是矩形的,这样障碍物的形状就被限制在固定的形式中。2. 其生成的路径不满足车辆曲率约束,使车辆难以顺利跟踪。为了扩大其适用范围,本文将障碍物分为三种类型:多边形障碍物、线性障碍物和点障碍物。在此基础上,提出了一种TPS+B算法,通过对障碍物进行凸化,提高TPS算法确定切点单元的能力。为了解决障碍物形状有限的问题,在障碍物为任意形状时,将障碍物顶点的单元坐标扩展为凸壳顶点的坐标。在使用b样条算法进行轨迹平滑时,可能会出现曲线轨迹与障碍物相交的情况。为避免这种情况,结合避障约束和曲率约束,设计了局部最优路径规划。这种设计的目的是对TPS算法的路径点进行移位,从而获得满足车辆曲率约束的无碰撞轨迹。在不考虑路径曲率约束的情况下,将a *、Dijkstra、快速探索随机树(RRT)、跳点搜索(JPS)和改进的TPS算法进行比较,结果表明改进的TPS算法在算法时间和路径长度上都达到了最优的性能。具体来说,在大尺度地图中,算法时间比JPS缩短了69.16%,路径长度比Dijkstra缩短了3.47%。在小比例尺地图中,算法时间缩短了39.16%,路径长度缩短了1.27%。在考虑路径曲率约束的情况下,将动态窗口方法(Dynamic Window Approach, DWA)与Hybrid a *算法进行比较,进一步证明TPS+B算法在算法时间和路径长度上都是最优的。在该场景下,在大规模地图中,算法时间比DWA减少97.56%,路径长度比Hybrid A*减少2.02%。在小比例尺地图中,算法时间缩短61.9%,路径长度缩短3.68%。实验结果证实了TPS+B算法在不同比例尺、不同障碍物地图路径规划中的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Path Planning Algorithm Based on Tangent Point Search and Constrained B-Spline

A Path Planning Algorithm Based on Tangent Point Search and Constrained B-Spline

The traditional Tangent Point Search (TPS) algorithm, as a path planning algorithm suitable for large-scale maps, performs well in the presence of large rectangular obstacles. However, it has two disadvantages: 1. it requires that the obstacles be rectangular so that the shape of obstacles is limited to the fixed form. 2. its resulting path does not meet the curvature constraints of vehicles so that it makes vehicles difficult to be tracked smoothly. To expand its scope of application, this paper categorizes obstacles into three types: polygonal obstacles, linear obstacles, and point obstacles. Based on this classification, a TPS+B algorithm is proposed to improve its ability to determine the tangent point cells in the TPS algorithm by convexifying the obstacles. To solve the problem of limited obstacle shapes, the cell coordinates of obstacle vertices are extended to the coordinates of convex hull vertices when the obstacles are arbitrary shapes. When using the B-spline algorithm for trajectory smoothing, the situation where the curved trajectory intersects with obstacles may occur. To avoid such a situation, the locally optimized path planning is designed by incorporating obstacle avoidance constraints and curvature constraints. The aim of such a design is to shift the path points of the TPS algorithm, thereby obtaining a collision-free trajectory that satisfies the vehicle's curvature constraints. Without considering the constraint of path curvature, a comparison of the A*, Dijkstra, Rapidly-exploring Random Tree (RRT), Jump Point Search (JPS), and the improved TPS algorithms reveals that the improved TPS algorithm achieves optimal performance in both algorithm time and path length. Specifically, in the large-scale map, the algorithm time is reduced by 69.16% compared to JPS, and the path length is shortened by 3.47% compared to Dijkstra. In the small-scale map, the algorithm time is reduced by 39.16%, and the path length is shortened by 1.27%. When considering the constraint of path curvature, a comparison between the Dynamic Window Approach (DWA) and Hybrid A* algorithms further demonstrates that the TPS+B algorithm remains optimal in both algorithm time and path length. In this scenario, in the large-scale map, the algorithm time is decreased by 97.56% compared to DWA, and the path length is reduced by 2.02% compared to Hybrid A*. In the small-scale map, the algorithm time is decreased by 61.9%, and the path length is reduced by 3.68%. The experimental results confirm the superiority of the TPS+B algorithm in path planning for different scale maps with various obstacles.

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来源期刊
Journal of Field Robotics
Journal of Field Robotics 工程技术-机器人学
CiteScore
15.00
自引率
3.60%
发文量
80
审稿时长
6 months
期刊介绍: The Journal of Field Robotics seeks to promote scholarly publications dealing with the fundamentals of robotics in unstructured and dynamic environments. The Journal focuses on experimental robotics and encourages publication of work that has both theoretical and practical significance.
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