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Particle Swarm Optimization for Route Planning of Unmanned Aerial Vehicles

机译:粒子群算法在无人机航路规划中的应用

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Route planning for unmanned aerial vehicle (UAV) is an extremely complex problem. Different means of optimization have been investigated for unmanned vehicles with various algorithms like genetic algorithms, evolution computations, neutral networks etc. This paper presents the application of Particle Swarm Optimization (PSO) for route planning problem. The route planning area is represented by a mesh of equal square cells. The objective function is constituted based on the factors of the flight time and safety. The threat level is evaluated with fuzzy technique. The implementation of the PSO search strategy to the route-planning problem is given. Simulation results indicate that the PSO based algorithm is a feasible approach for route planning problem.
机译:无人驾驶飞机(UAV)的路线规划是一个极其复杂的问题。研究了各种无人驾驶车辆的不同优化方法,其中包括遗传算法,进化计算,中立网络等各种算法。本文介绍了粒子群优化(PSO)在路线规划问题中的应用。路线规划区域由相等正方形单元格的网格表示。目标函数是根据飞行时间和安全性因素构成的。使用模糊技术评估威胁级别。给出了针对路径规划问题的PSO搜索策略的实现。仿真结果表明,基于PSO的算法是解决路线规划问题的一种可行方法。

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