摘要
为解决三维环境下的无人机航迹规划问题,提出一种基于改进人工鱼群算法的无人机航迹规划方法。构建规划空间与威胁模型,依据威胁模型提出导航点自适应选择算法,确定其位置与个数,对航迹进行编码;综合考虑无人机航程、威胁代价、爬升代价以及转弯约束,设计航迹代价函数;采用视野自适应策略改进人工鱼群算法进行航迹寻优,得到航迹。仿真结果表明,与粒子群算法相比,采用改进的人工鱼群算法进行无人机三维航迹规划更有效,代价更小。
To solve the problem of unmanned aerial vehicle(UAV)trajectory planning in the three-dimensional environment,an improved artificial fish swarm algorithm was proposed.The planning space and threaten model were constructed.An adaptive selection algorithm was proposed to determine the location and number of the navigation point,according to the threaten model.On this basis,the trajectory was coded.The comprehensively trajectory cost function of UAV was designed in terms of the airrange,threaten cost,climbing cost and turning constraint.The vision adaptive strategy was adopted to improve artificial fish swarm algorithm for trajectory optimization.Simulation results show that compared with particle swarm algorithm,it is more effective and less cost to use the improved artificial fish swarm algorithm for 3 Dtrajectory planning optimization of UAV.
引文
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