基于Dijkstra和蚁群优化的机器人路径规划研究

2019 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2019-11-01 DOI:10.1109/ICIIBMS46890.2019.8991502

Zhen Nie, Huailin Zhao

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引用次数: 15

摘要

本文研究了已知环境下的路径规划问题。根据Dijkstra算法和蚁群算法，设计了一种混合路径搜索算法。基于可视化图法构建的环境模型，采用Dijkstra算法进行初始路径规划。然后对蚁群算法进行改进，对初始路径进行优化，使机器人的路径最小。MATLAB仿真表明，基于Dijkstra-ACO的路径规划算法具有较高的路径搜索效率和良好的路径规划效果。该算法是有效可行的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Research on Robot Path Planning Based on Dijkstra and Ant Colony Optimization

In this paper, the path planning problem in known environments was studied. According to Dijkstra algorithm and ant colony optimization (ACO), we designed a hybrid algorithm to search the path. Based on the environment model, constructed by using visual graph method, Dijkstra algorithm was used for initial path planning. Then the ACO was improved and used to optimizes the initial path to minimize the path of the robot. The simulation on MATLAB showed that the path planning algorithm based on Dijkstra-ACO has higher efficiency of path search and good effect of path planning. The algorithm is effective and feasible.

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2019 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)

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