| 基于人工势场法优化的蚁群无人机航路规划 |
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| 引用本文： | 王芳,;李昆鹏.基于人工势场法优化的蚁群无人机航路规划[J].西安航空技术高等专科学校学报,2014(5):64-68. |
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| 作者姓名： | 王芳 ;李昆鹏 |
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| 作者单位： | [1]西安航空学院航空工程系,陕西西安710077; [2]长安大学机械学院,陕西西安710064 |
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| 基金项目： | 西安航空学院校级科研项目（12XP818） |
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| 摘 要： | 针对复杂环境下无人机航路规划问题,提出一种势场法优化的蚁群航路规划算法。为了改善蚁群初始路径搜索过程中的盲目性,将人工势场法的规划结果作为先验知识,对蚁群初始到达的栅格进行邻域信息素的初始化,进而运用改进的蚁群算法完成航路搜索任务。仿真结果表明,新算法具有收敛速度快,规划路径短以及环境自适应的优点。
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| 关 键 词： | 航路规划 蚁群算法 人工势场 转移概率 |
Ant Colony Algorithm Based on the Optimization of Potential Field Method for Unmanned Aircraft Path Planning |
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| Institution: | WANG Fang, LI Kun-peng (1. Department of Aviation Engineering, Xi＇an Aeronautical University, Xi＇an 710077, China; 2. School of Mechanical Engineering, Changan University, Xi＇an 710064, China) |
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| Abstract: | To realize unmanned aircraft path planning in complicated environments, a new potential field optimal ant colony algorithm for path planning is presented. To further quicken the convergence speed of AC, the path planning results of potential field method are taken as the prior knowledge first, and the originally reached grids is initialized by neighborhood pheromone. Then, it can use AC to finish the entire period of path searching, and eliminate the blindness in the searching process. Simulation results indicate that the proposed algorithm （APFOA） is characterized by high convergence speed, short planning path and self-adaptation. |
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| Keywords: | path planning ant colony algorithm artificial potential field transition probability |
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