基于双向迪杰斯特拉算法移栽机补栽路径规划及仿真

doi:10.13733/j.jcam.issn.2095-5553.2023.03.025

摘要/Abstract

摘要： 为提高移栽机补栽作业的自动化水平，对移栽机补栽路径规划进行研究。首先，对移栽机补栽进行分析并建立路径规划仿真地图；然后，提出一种双向迪杰斯特拉算法，并进行二次优化实现节点排序，配合A*算法的避障功能实现路径；最后，基于C++编程及OpenCV实现算法功能并进行图像绘制实现算法仿真。仿真结果表明：采用改进后的双向迪杰斯特拉算法规划路径，路径移动距离平均下降14.74%，转向次数平均减少8%，移动时间平均减少13.41%。双向迪杰斯特拉算法，相比迪杰斯特拉算法规划的目标节点顺序更优。因此，改进后的算法能实现移栽机补栽更优的路径规划，提升移栽机补栽效率，为补栽路径规划问题的研究提供重要参考。

关键词: 移栽机, 补栽, 路径规划, 避障算法, 迪杰斯特拉算法

Abstract: In order to improve the automation level of transplanting machine replanting operation, the path planning of transplanting machine replanting was studied. Firstly, the replanting of transplanting machine was analyzed and the path planning simulation map was established. Then, a bidirectional Dijkstra algorithm was proposed, and the secondary optimization was carried out to realize the node sorting, and the obstacle avoidance function was realized with the A* algorithm. Finally, based on C++ programming and OpenCV, the algorithm function was realized and the algorithm simulation was realized by image rendering. The simulation results show that using the improved twoway Dijkstra algorithm to plan the path, the path moving distance decreases by 14.74% on average, the number of turns decreases by 8% on average, and the moving time decreases by 13.41% on average. Bidirectional Dijkstra algorithm is better than Dijkstra algorithm in planning target node order. Therefore, the improved algorithm can realize better path planning of transplanting machine replanting, improve the efficiency of transplanting machine replanting, and provide an important reference for the research of replanting path planning.

Key words: transplanter, replanting, path planning, obstacle avoidance algorithm, Dijkstra algorithm

中图分类号:

S223.92

冯莉, 吕修凯, 崔生乐, 杨春梅, 徐晓燕. 基于双向迪杰斯特拉算法移栽机补栽路径规划及仿真[J]. 中国农机化学报, 2023, 44(3): 177-182.

Feng Li, Lü Xiukai, Cui Shengle, Yang Chunmei, Xu Xiaoyan. Path planning and simulation of transplanting machine replenishment based on twoway Dijkstra algorithm[J]. Journal of Chinese Agricultural Mechanization, 2023, 44(3): 177-182.

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