The Study And Implement On Three-dimensional UAV Path Planning Based On Improved Ant Colony Algorithm

With the development of small unmanned aerial vehicle(UAV),the application of UAV has expanded from the military to the civil fields.In the field of civil aviation,UAV is generally used as an auxiliary tool to deal with urban problems,and building is the main factor to hinder UAV flight.So it is necessary to find the optimal path for UAV to fly under certain constraints.Most of the traditional path planning problems are based on 2D environment,and solutions are mature.3D path planning has become a new research focus recently.When the environment is extended from 2D to 3D,it will bring a lot of problems.3D environment is a broad space and UAV faces more threat in it.Ant colony algorithm has good search ability and good performance for multi optimization problems.It is a popular direction of intelligent algorithm in path planning.According to the present situation of UAV path planning,a 3D path planning method is proposed in this paper.It is based on improved ant colony algorithm.First,this paper analyses the research status of UAV.After stating the key problems of path planning,we summarize the difficulties of current research and instruct the relevant background knowledge.Secondly,we design a hierarchical model which concludes vertical and horizontal planning model.It transfers 3D path planning to 2D path planning.After the elaboration of optimization in vertical model,this paper create flyable path for UAV.Thirdly,after studying the ant colony algorithm and combing the characteristics of hierarchical model,this paper make an optimization by adding height heuristic function and changing transfer rules.It improves the adaptability of ant colony algorithm in new model.Aiming at solving security issue of UAV,this paper add a security factor to optimize the algorithm and change path.Then this paper design security evaluation to indicate the degree of safety of the path.Finally,the proposed algorithm and model are used to simulate the UAV path planning,and compared with the basic ant colony algorithm.Experimental results verify the effectiveness of the research.