针对代价函数权重需要根据环境变化而变化的问题,结合飞行约束条件提出归一化的代价函数,当环境发生变化时,不用再修改代价函数,增强了算法的鲁棒性。为了弥补传统定步长寻径算法耗时长的缺陷,设计了一种基于B样条曲线与遗传算法的高时效寻径算法。利用遗传算法在地图中所寻合适的控制点,再结合B样条曲线生成航路。为了增强遗传算法的全局搜索能力,遗传算法中加入振动法则,使得种群在进化中后期依旧保持一定的多样性。仿真结果表明该算法与精英蚁群算法相比,规划时间大幅缩短;与振动遗传算法相比,航路代价明显降低。
Concerning the weight of cost function has to change with the environment ,a normalized cost function is designed with flight constraints in this paper,which could improve the robustness of the algorithm since there is no need to modify the cost function when the environment is changed. A high timeliness routing algorithm is proposed which is based on B-spline curve and Genetic Algorithm(GA) to reduce the time cost of traditional fixed step algorithms. First,the control points are searched by GA in the map. Then the whole path is produced by B-spline curve with control points. An appropriate vibrantion law is added in order to enhance the global search ability of GA so that the population still maintains a certain diversity in the evolution of the late. Simulation result shows that the method is much faster than Elite Ant Algorithm and the cost of flight route is obviously lower than that of Vibrational Genetic Algorithm.