基于改进人工蜂群算法的无人机路径规划研究

Research on UAV Path Planning Based on Improved Artificial Bee Colony Algorithm

针对传统无人机路径规划算法存在收敛速度慢、效率低以及易陷入局部最优的缺点,本文提出了一种改进的人工蜂群路径规划算法。首先利用佳点集的方式生成初代蜜源位置,保证蜜源信息的多样性和均匀性;接着在采蜜蜂搜索机制中引入自适应动态调节因子,加强了算法前期的全局寻优能力和后期的局部寻优能力;最后,采用大步长搜索机制加强侦查蜂的寻优效果。仿真结果显示,改进后的算法寻优能力得到了显著的提高。

Aiming at the shortcomings of traditional UAV path planning algorithm, such as slow convergence speed, low efficiency and easy to fall into local optimum, this paper proposes an improved artificial bee colony path planning algorithm. First, the location of the first-generation nectar source is generated by the method of good point set to ensure the diversity and uniformity of nectar source information;then, an adaptive dynamic adjustment factor is introduced into the bee-picking search mechanism, which strengthens the global optimization ability in the early stage of the algorithm and the local search in the later stage. Finally, a large-step search mechanism is used to enhance the optimization effect of scout bees. The simulation results show that the optimization ability of the improved algorithm has been significantly improved.