UAV 3D Path Planning based on Ant Colony Algorithm

Path planning technology is the core part of UAV field, the purpose of path planning is to provide a feasible and safe optimal path for UAV flight, to meet the feasibility of UAV operation, and improve the path optimization ability of UAV in complex and multi-obstacle environment. Traditional path planning algorithms have low computational efficiency and are prone to local extremes. In this paper, it is proposed that the three-dimensional path planning of UAV based on ant colony algorithm can improve the effectiveness of UAV dynamic constraint processing and enhance the path optimization ability in multi-obstacle environment. The advantages of this algorithm are fast convergence speed, simple calculation process, and few parameters, etc., and it has become the first choice for UAV planning three-dimensional path. At the same time, a multi-obstacle model is constructed in a three-dimensional environment, and the fitness function is constructed on the obstacle threat, path length and navigation height integration. After dynamic 3D environment simulation experiments, the results show that the ant colony algorithm can significantly improve the UAV path optimization ability and ensure the stability of 3D path planning.