基于改进遗传算法的多无人机路径规划

对多无人机在动态环境下的路径规划问题进行了分析与建模，模型将无人机区分为就绪、工作、返航、失控4种状态；考虑了机群工作效率和威胁区域的生存概率，提出一种基于改进遗传算法的多无人机的路径规划方法。方法设计了新的编码、解码方法和具有明确物理意义的适应度评价函数，以加快实时的运算速度和提高运算精度。通过计算机仿真表明方法具有良好的多无人机动态路径规划能力。

Path Planning of Multiple UAVs Based on a Improved Genetic Algorithm

Path planning of multiple UAVs in the dynamic environment is analyzed and modeled. 4 states ： ready-state, working- state, homing- state and incontrollable-state are defined. Working efficiency of UAVs and survival probability in the threats are taken into account. Based on that, the paper proposed a method of path planning of Multiple UA- Vs based on hybrid genetic algorithm. This method designs new coding methods and fitness functions with definite physical meaning so that the realtime operation speed and operation precision can be accelerated and improved respectively. Computer simulation experiments show that, the method has good path planning ability for multiple UAVs in the dynamic environment.