Three-Dimensional UAV Path Planning Based on Improved Constrained State Transition Algorithm

Unmanned aerial vehicles (UAVs) have been widely used in various fields. The UAV path planning is an important part of the UAV autonomous control system. However, the results of the traditional UAV path planning methods are unsafe and infeasible in complex three-dimensional flight environment. In this paper, a novel UAV path planning method based on improved constrained state transition algorithm is presented for solving this problem. In the proposed method, the three-dimensional UAV path planning in complex flight environment is constructed as a constrained optimization problem. The improved constrained state transition algorithm with mutation scheme (ICSTA) is proposed, which has an excellent global search capability and maintains the diversity of the population. The proposed method based on ICSTA obtains a safe and feasible optimal flight path in the simulation, whose superior performance is also verified.