| 基于优化蚁群算法的机器人路径规划 |
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| 引用本文： | 任春明,张建勋.基于优化蚁群算法的机器人路径规划[J].计算机工程,2008,34(15):1-3,35. |
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| 作者姓名： | 任春明 张建勋 |
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| 作者单位： | 1. 南开大学信息技术与科学学院,天津,300071;天津财经大学信息科学与技术系,天津,300222
2. 南开大学信息技术与科学学院,天津,300071 |
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| 基金项目： | 国家"863"计划基金资助项目"家用保安机器人共性单元部件及技术的研发" |
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| 摘 要： | 研究机器人导航中的路径规划问题，运用栅格法和图论思想建立环境模型，在该模型中通过蚁群算法进行路径寻优，提出用遗传算法的思想改进已有蚁群算法，即GAA算法。仿真实验结果表明，该算法能有效地提高机器人的路径搜索速度及路径优化、路径平滑等方面的指标。
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| 关 键 词： | 优化蚁群算法 GAA算法 路径规划 |
Robot Path Planning Based on Improved Ant Colony Optimization |
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| REN Chun-ming,ZHANG Jian-xun.Robot Path Planning Based on Improved Ant Colony Optimization[J].Computer Engineering,2008,34(15):1-3,35. |
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| Authors: | REN Chun-ming ZHANG Jian-xun |
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| Affiliation: | (1. College of Information Technical and Science, Nankai University, Tianjin 300071; 2. Department of Information Science and Technology, Tianjin University of Finance and Economics, Tianjin 300222) |
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| Abstract: | This paper mainly researches the problem of path planning in navigation of robot. The algorithm describes the environment of robot making use of grid division. In this environment, Ant Colony Optimization(ACO) is used to do path planning. The ACO is improved by the idea of Genetic Algorithm(GA), GAA algorithm is presented. Simulation results show that the method can effectively improve the speed of path searching, path optimizing and path smoothness. |
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| Keywords: | Ant Colony Optimization(ACO) GAA algorithm path planning |
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