| Global optimal path planning for mobile robot based on improved Dijkstra algorithm and ant system algorithm |
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| 作者姓名： | 谭冠政 贺欢 Aaron Sloman |
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| 作者单位： | [1]School of Information Science and Engineering, Central South University, Changsha 410088, China [2]School of Computer Science, The University of Birmingham, Birmingham B15 2TT, UK |
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| 基金项目： | Project（50275150） supported by the National Natural Science Foundation of China; project（20040533035） supported by the National Research Foundation for the Doctoral Program of Higher Education of China |
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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 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.
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| 关 键 词： | 移动机器人 路径规划 遗传算法 优化 |
| 文章编号： | 1005-9784（2006）01-0080-07 |
| 收稿时间： | 2005-06-10 |
| 修稿时间： | 2005-09-15 |
Global optimal path planning for mobile robot based on improved Dijkstra algorithm and ant system algorithm |
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| Tan Guan-zheng , He Huan and Aaron Sloman.Global optimal path planning for mobile robot based on improved Dijkstra algorithm and ant system algorithm[J].Journal of Central South University of Technology,2006,13(1):80-86. |
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| Authors: | Tan Guan-zheng He Huan and Aaron Sloman |
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| Affiliation: | (1) School of Information Science and Engineering, Central South University, 410083 Changsha, China;(2) School of Computer Science, The University of Birmingham, B15 2TT Birmingham, UK |
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| Abstract: | 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. |
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| Keywords: | mobile robot global optimal path planning improved Dijkstra algorithm ant system algorithm MAKLINK graph free MAKLINK line |
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