Path planning of UAV in mountain area’s forest rescuing
Lifeng Liu, Fei Yang, Zhiyong Wang · IOP Conference Series Materials Science and Engineering · 2019
In forest rescuing, unmanned aerial vehicle(UAV) can not save all the areas at a time due to the influence of its physical properties and risk factor. So it is extremely important to bring the service efficiency of the UAV into full play. The optimal path planning problem of the UAV for forest rescuing is presented and a mathematic model of the problem is built up. On the basis of this, a fuzzy clustering -PSO - genetic algorithm is presented. The computational amount is decreased, a method combined of both the shortest distance and point clustering is adopted. The simulation test result indicates that when task number less than 30, particle swarm algorithm is superior to genetic algorithm, and vice versa. Both methods plan the same airline but time, and it can resolve the path planning problem of the UAV for water environmental monitoring effectively.