系统工程与电子技术 ›› 2024, Vol. 46 ›› Issue (4): 1364-1371.doi: 10.12305/j.issn.1001-506X.2024.04.25

• 制导、导航与控制 • 上一篇    下一篇

改进双向快速搜索随机树的无人艇路径规划

赵贵祥1, 周健2, 李云淼1, 王晨旭1,*   

  1. 1. 天津大学海洋科学与技术学院, 天津 300110
    2. 江苏自动化研究所, 北京 100036
  • 收稿日期:2023-03-13 出版日期:2024-03-25 发布日期:2024-03-25
  • 通讯作者: 王晨旭
  • 作者简介:赵贵祥(1998—), 男, 硕士研究生, 主要研究方向为水面无人艇路径规划和避障技术
    周健(1996—), 男, 工程师, 硕士, 主要研究方向为航海安全保障和智能船舶
    李云淼(2000—), 女, 硕士研究生, 主要研究方向为水面无人艇路径规划和避障技术
    王晨旭(1984—), 男, 讲师, 博士, 主要研究方向为海洋结构物航行安全性能、水面无人艇避碰

Improved bi-directional rapidly-exploring random tree path planning for USV

Guixiang ZHAO1, Jian ZHOU2, Yunmiao LI1, Chenxu WANG1,*   

  1. 1. School of Marine Science and Technology, Tianjin University, Tianjin 300110, China
    2. Jiangsu Autonation Research Institute, Beijing 100036, China
  • Received:2023-03-13 Online:2024-03-25 Published:2024-03-25
  • Contact: Chenxu WANG

摘要:

针对双向快速搜索随机树(bidirectional rapidly-exploring random tree, BI-RRT)算法在全局路径规划时存在搜索效率低、路径拐点较多等问题, 提出一种改进BI-RRT的水面无人艇(unmanned surface vehicle, USV)全局路径规划算法。该算法采取了极度贪心的思想、高斯偏置随机点采样方法以及启发式的节点扩展策略, 同时对节点扩展和搜索树连接进行角度约束, 将生成的路径进行剪枝和3次B样条优化处理。结果表明, 相对于改进前, 改进的BI-RRT在平均时间、随机采样点和平均路径上分别减少了40.5%、65.0%和24.0%。改进后的算法时间、采样点和搜索树扩展大幅度减少, 路径平滑度提高且路径更短。

关键词: 路径规划, 水面无人艇, 双向快速搜索随机树, 高斯偏置随机点, 角度约束

Abstract:

Aiming at the problems of bi-directional rapidly-exploring random tree (BI-RRT) algorithm in global path planning, such as low search efficiency and many turning points, an improved BI-RRT algorithm for global path planning of unmanned surface vehicle (USV) is proposed. The proposed algorithm adopts the idea of extreme greed, a Gaussian biased random point sampling method and a heuristic node expansion strategy. The node expansion and search tree connection are also angularly constrained, and the generated paths are cut and optimized with three B-samples. The results show that the improved BI-RRT reduces the average time, random sampling points, and average path by 40.5%, 65.0%, and 24.0%, respectively, compared to the previous BI-RRT. The improved algorithm has a significant reduction in time consumption, sampling points and search tree expansion, with improved path smoothing and shorter paths.

Key words: path planning, unmanned surface vehicles (USV), bi-directional rapidly-exploring random tree (BI-RRT), Gaussian biased random points, angular constraints

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