Path planner for unmanned aerial vehicles based on modified PSO algorithm
Zhu Hongguo, Zheng Changwen, Xiaohui Hu, Xiang Li · 2008
Most path planning algorithms existed have disadvantages in space representation, constraints handling or computation efficiency. Combining particle swarm optimization with path planning problem for unmanned aerial vehicles (UAVs), a new path planner for aerial vehicles based on modified PSO algorithm is presented. Path planning problem is modeled as a 5-element array. Incorporating constraints into fitness evaluation reduces search space while a modified PSO algorithm is introduced to improve global optimization performance. Experiment results demonstrate that the proposed method is able to solve path planning problem effectively and provide a feasible path in a short time.