Application of Ant Algorithm to Path Planning of Unmanned Aerial Vehicle
Qiu Yong-cheng · Jisuanji fangzhen · 2010
To solve the problems such as local optimum and long searching time in ACA( Ant Colony Algorithm),an improved Ant Colony Optimization Algorithm for UAV(Unmanned Aerial Vehicle) is proposed.It uses recent node selection strategy to optimize the path and improve search efficiency,thus make it suitable for large scale problem. It modifies the rule of updating pheromones and volatile factor in the latter adapted to solve the algorithm,so that the increment of pheromone after every round of search can better reflect the quality of solution to effectively avoid local optimum and quicken the convergence. The simulation results for part of the UAV problems show that the improved ant colony algorithm for solving the optimal solution and convergence properties has achieved very good results. Therefore,this Ant Colonv Optimization Algorithm is proved to be feasible and effective.