多无人机平滑巡检路径规划算法
Smooth Inspection Path Planning Algorithm for Multiple Unmanned Aerial Vehicles
徐小玲 1雷高伟 1刘美1
作者信息
- 1. 广东石油化工学院自动化学院,茂名 525000
- 折叠
摘要
针对石化中多无人机巡检路径问题,利用Dubins曲线并采用提出的滚动式分支定界算法实现最短的平滑轨迹规划.算法将多无人机巡检路径规划问题描述为基于Dubins的多旅行商问题,以实现最优巡检路径规划为目标,提出滚动式分支定界算法不断预估并更新路径长度,并利用上界及下界的不断迭代优化寻求最优路径.此外,算法利用最小插入算法对贪婪算法的改进获得优质的候选解从而剔除更多分支来优化巡检路径.最后,通过离散化各监测点位置的航向角及滑动窗口的限制来规划Dubins路径,实现路径平滑.实验仿真结果表明与现有的巡检路径规划算法相比,该算法在路径长度方面具有更好的性能.
Abstract
The path planning algorithm was proposed for multiple unmanned aerial vehicles in the petrochemical industry,aiming to find the shortest smooth inspection path.The problem was modeled as a multiple traveling salesman problem based on Dubins curve.It was achieved by using Dubins curve and the rolling branch-and-bound algorithm.To achieve the optimal inspection path planning,the rolling branch-and-bound algorithm was proposed to update the path length constantly,and the optimal path was sought by continuous iterative optimization of the upper and lower bounds.Besides,the algorithm combined the minimum insertion algorithm with the greedy algorithm to obtain better candidate solutions to prune more branches and optimize the inspection path.And then,the smooth Dubins path was planned by discretizing the heading angle of each grid cell and using the sliding window.Simulation results demonstrate that the proposed algorithm has better performance in terms of exploration time compared to other existing inspection path planning algorithms.
关键词
路径规划/无人机/Dubins/滚动式分支定界Key words
path planning/unmanned aerial vehicle(UAV)/Dublins/rolling branch-and-bound引用本文复制引用
基金项目
国家自然科学基金(62073091)
广东省高校重点领域专项(2020ZDZX3042)
广东石油化工学院人才引进项目(XJ2023000402)
出版年
2024
NETL
NSTL
万方数据