运动规划
计算机科学
沃罗诺图
人工蜂群算法
战场
趋同(经济学)
算法
适应性
路径(计算)
数学优化
收敛速度
人工智能
机器人
数学
几何学
经济增长
生态学
程序设计语言
古代史
经济
频道(广播)
计算机网络
历史
生物
摘要
Due to the complex constraints, more uncertain factors and critical real-time demand of path planning for multiple unmanned surface vehicle (multi-USV), an improved artificial bee colony (I-ABC) algorithm were proposed to solve the model of cooperative path planning for multi-USV. First the Voronoi diagram of battle field space is conceived to generate the optimal area of USVs paths. Then the chaotic searching algorithm is used to initialize the collection of paths, which is regard as foods of the ABC algorithm. With the limited data, the initial collection can search the optimal area of paths perfectly. Finally simulations of the multi-USV path planning under various threats have been carried out. Simulation results verify that the I-ABC algorithm can improve the diversity of nectar source and the convergence rate of algorithm. It can increase the adaptability of dynamic battlefield and unexpected threats for USV.
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