Collaborative Traversal Path Planning Algorithm of for Multiple Unmanned Survey Vessels
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摘要: 为了实现对岛礁及周围海域水下地貌信息的获取, 同时使用多个无人扫测艇进行协同测绘以提高测绘效率, 文中提出一种协同遍历路径规划算法: 采用扫描线多边形方法得到动态栅格地图, 建立水域环境模型, 基于K-means++算法对任务区域进行分配, 分配区域内使用启发式路径规划算法得到完全遍历路径。 仿真结果满足区域分配的均匀性和遍历路径的连通性要求。在此基础上提出了动态重规划算法, 根据实时可工作无人艇数量对未遍历区域进行重分配。仿真结果证明, 在不同间距的栅格地图中, 协同遍历算法均提高了测绘效率, 路径重复率较低, 可以快速高效地实现动态重规划。
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关键词:
- 无人扫测艇 /
- 协同 /
- K-means++算法 /
- 遍历路径规划 /
- 动态重规划
Abstract: To obtain underwater geomorphological information of islands, reefs, and surrounding waters and improve surveying and mapping efficiency, collaborative surveying, and mapping using multiple unmanned survey vessels should be employed. In this study, a collaborative traversal path planning algorithm in conjunction with the scanline polygon method is used to obtain a dynamic grid map. A water environment model is then constructed, task areas are allocated based on the K-means++ algorithm, and a full traversal path is obtained by the heuristic path planning algorithm. Simulation results meet the requirements of uniformity and connectivity of the traversal path. A dynamic reprogramming algorithm is then proposed to reallocate the untraversed areas based on the number of unmanned vessels that can work in real time. The collaborative traversal algorithm is shown to improve the mapping efficiency of the grid map with different spacing, and the path repetition rate is low, meaning that dynamic reprogramming can be realized quickly and efficiently. -
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