Urban UAV Path Planning Based on Multi-object Particle Swarm Optimization
Aiming at the problem of unmanned aerial vehicle(UAV)path planning in urban environ-ments,a multi-objective path planning model is proposed.This model aims to maximize UAV operational efficiency while minimizing operational risk,considering UAV performance constraints,noise constraints,and obstacle avoidance requirements.Furthermore,using random speed update and inertia factor dynamic adjustment strategy to improve the particle swarm optimization algorithm.The individual and group ex-treme values are updated based on the crowded distance of the Pareto solution set,and the Pareto solution set is constructed to obtain multiple sets of candidate path solutions.Finally,the feasibility and effective-ness of the proposed method are verified through simulation.
万方数据
维普
