| 固定翼巡线无人机实时蚁群算法路径规划 |
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| 引用本文：郑武略1，尚 涛2，金 钊3.固定翼巡线无人机实时蚁群算法路径规划[J].计算技术与自动化,2017,(2):109-112 |
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| 中文摘要:本文针对传统蚁群算法局部早熟等问题对算法进行了改进，并对无人机路径规划及重规划多条件约束问题进行了研究，提高蚁群算法航迹规划计算速度及全局性来满足实时蚁群算法航迹规划要求。文章针对传统蚁群算法的早熟问题采用全局与局部信息素互补衰减法，来高效完成蚁群算法寻优问题，并当无人机偏离航线时能及时根据无人机所在位置重新规划。通过实验结果得出蚁群算法具有快速的计算能力，能在短时间内对更改的路径进行响应，完成无人机自校正航迹规划。 |
| 中文关键词:无人机 实时路径规划 蚁群算法 |
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| Online Path Planning Offixed Wing with Ant Colony Algorithm in Line Patrol |
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| Abstract:Because of premature in traditional ACO(Ant Colony Optimal)，this article comes up with a improved algorithm and use this algorithm to realize the multifactor control in UAV online path planning to improve the speed and global search. By combing local evaporation with global pheromone update，the ACO has a higher speed in finding optimal planning path. What’s more，it’s suit for the self adjust UAV path planning. Through the improving ACO，a more precise and efficiency path can be found. |
| keywords:unmanned aerial vehicle(UAV) path planning online ant colony optimal(ACO) |
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