基于多目标鸽形优化和差分进化的无人机路径规划方法

Bingda Tong, Lin Chen, H. Duan
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引用次数: 9

摘要

受鸽子群行为的启发,提出了一种基于鸽子优化和差分进化的无人机路径规划和自主编队改进方法。首先,将无人机路径规划的数学模型设计为包含路径长度、路径弯曲度和路径风险三个指标的多目标优化模型;在此基础上,提出了将鸽类优化与差分进化的突变策略相结合的可行路径优化方法。此外,利用Pareto优势选择鸽子的全局最优位置。最后,通过与标准粒子群优化算法和标准差分进化算法的仿真对比,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A path planning method for UAVs based on multi-objective pigeon-inspired optimisation and differential evolution
Inspired by the behaviour of pigeon flocks, an improved method of path planning and autonomous formation for unmanned aerial vehicles based on the pigeon-inspired optimisation and differential evolution is proposed in this paper. Firstly, the mathematical model for UAV path planning is devised as a multi-objective optimisation with three indices, i.e., the length of a path, the sinuosity of a path, and the risk of a path. Then, the method integrated by pigeoninspired optimisation and mutation strategies of differential evolution is developed to optimise feasible paths. Besides, Pareto dominance is applied to select the global best position of a pigeon. Finally, a series of simulation results compared with standard particle swarm optimisation algorithm and standard differential evolution algorithm show the effectiveness of our method.
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