针对使用基于网格划分策略的改进人工鱼群算法计算无人机路径规划问题中寻优精度与算法计算量的矛盾,提出一种改进人工鱼群算法,该算法引入自适应步长和执行概率自适应分段网格遍历策略。算法前期用较大步长全局搜索较优路径,后期用较小步长及网格分段遍历策略在较优解附近进行局部遍历得到更精确最优解。仿真结果表明所提改进人工鱼群算法比原始鱼群算法和自适应步长人工鱼群算法结果更精确、稳定,较基于简单网格划分策略的人工鱼群算法计算量更小。

To resolve the conflict between precision and workload in path planning of an UAV with artificial fish-swarm algorithm based on gridding method, an improved artificial fish-swarm algorithm was presented. The proposed algorithm introduces adaptive step length method and adaptive gridding segmented traversal method. In early iteration, the proposed algorithm calculates with large step length, later calculates with narrowed step length and gridding segmented traversal method to find a better solution around a defective solution. The simulation result shows that the proposed artificial fish-swarm algorithm is more accurate and more stable than basic artificial fish-swarm algorithm or adaptive step length artificial fish-swarm algorithm and has large advantage on workload over artificial fish-swarm algorithm based on gridding method.