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Global optimal path planning for mobile robot based onimproved Dijkstra algorithm and ant system algorithm 被引量:20

Global optimal path planning for mobile robot based onimproved Dijkstra algorithm and ant system algorithm
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摘要 A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning. A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAK-LINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.
出处 《Journal of Central South University of Technology》 EI 2006年第1期80-86,共7页 中南工业大学学报(英文版)
基金 Project(50275150)supportedbytheNationalNaturalScienceFoundationofChina project(20040533035)supportedbytheNationalResearchFoundationfortheDoctoralProgramofHigherEducationofChina
关键词 移动机器人 路径规划 遗传算法 优化 mobile robot global optimal path planning improved Dijkstra algorithm ant system algorithm MAKLINK graph free MAKLINK line
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