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针对当前使用的无人机航迹规划代价函数的不足之处,提出一种利用遗传算法对无人机航迹规划代价函数进行优化的方法。对基本遗传算法进行了局部改进,设计了航迹极坐标编码方式及航迹适应度函数,在采用基本遗传操作算子的基础上采取精英保存策略,提高了算法的效率;采用代价归一化并进行优化的思想,得到优化之后的代价函数权重值。优化结果表明,该方法可以获得代价更低的航迹。
In view of the shortcomings of the cost function of UAV trajectory planning currently used, a genetic algorithm is proposed to optimize the trajectory planning cost function of UAV. The basic genetic algorithm was improved locally. The polar coordinate encoding and trajectory fitness functions were designed. Based on the basic genetic operators, the elitist preservation strategy was adopted to improve the efficiency of the algorithm. Using the cost normalization And optimize the idea, get the weight value of the cost function after optimization. The optimization results show that this method can get a lower cost trajectory.