Path Planning for UAVs Based on Improved GA Algorithm
Liu Huixia · Jisuanji fangzhen · 2011
The problem of the UAVs path planning is to gain extreme values under multiple constraints in essence.Avoiding local optimal solution and reducing calculating time are the key techniques for the path planning algorithms.The traditional algorithms converge slowly and fall into local optimal solution easily.So an improved GAAA Algorithm is presented in this paper.Minor mutation and introducing new colony operators are given in the genetic algorithm to maintain multiple colonies.In the ant algorithm phase,we present a rule of obtaining the initial pheromone based on path cost,which guarantees better initial pheromone distribution and avoids fall into local optimal solution.Compared with other algorithms,the simulation results show that our algorithm improves the convergence greatly,and can obtain better path with less time.