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计算机系统应用英文版:2013,22(1):200-203
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基于遗传算法的UAV自适应航迹规划
(南昌航空大学 信息工程学院, 南昌 330063)
Adaptive Path Planning of the UAV Based on Genetic Algorithm
(College of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China)
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Received:June 18, 2012    Revised:August 13, 2012
中文摘要: 根据遗传算法与动态的稀疏A*搜索(Dynamic Sparse A* Search, DASA)算法各自的特点, 提出一种组合优化算法来实现在不确定战场环境中自适应航迹规划. 在无人机(UAV, Unmanned Aerial Vehicles)飞行前, 采用全局搜索能力强的遗传算法进行全局搜索, 对从起始点到目标点的飞行航线进行规划, 生成全局最优或次优的可行参考飞行航线; 在无人机任务执行阶段, 以参考飞行航线为基准, 采用DASA算法进行在线实时航迹再规划. 仿真结果表明, 与遗传算法相比, 该组合算法不但能生成近似最优解, 而且能够满足在线实时应用的要求.
Abstract:According to the characteristics of genetic algorithm and the Dynamic Sparse A* Search (Dynamic Sparse A* Search, DASA) algorithm, this paper puts forward a combinational optimal algorithm fulfilling adaptive path planning in flying environment with unknown threat. Before flight, the ground station adopt genetic algorithm which possess the powerful ability of global search to realize Universal Search, we proceed programme from the starting point to the target point to generate the global optimal or suboptimal feasible reference airline. When the UAV is executing fly missions, DASA algorithm is used for on line route re planning based on the reference flight line as the benchmark. The simulation results show that compared with the genetic algorithm, the combined algorithm cannot only produce an approximate optimal solution, but also meet the requirements of real-time online application.
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王琪,马璐,邓会亨.基于遗传算法的UAV自适应航迹规划.计算机系统应用,2013,22(1):200-203
WANG Qi,MA Lu,DENG Hui-Heng.Adaptive Path Planning of the UAV Based on Genetic Algorithm.COMPUTER SYSTEMS APPLICATIONS,2013,22(1):200-203