3D real-time path planning based on cognitive behavior optimization algorithm for UAV with TLP model

Real-time path planning of unmanned aerial vehicle (UAV) in the three-dimension environment is a complicated global optimum problem. This paper formulates the real-time path planning problem for the unmanned aerial vehicles (UAVs) as a complicated global optimum problem in the three-dimensional environment and proposes an improved a tree-dimensional (3D) real-time path planning algorithm based on tri-level programing model to generate an optimal feasible route. The flight routeis designed to have a short length and a low flight altitude. The multiple constraints based on the realistic scenarios are taken into account as the threat level function. Firstly, from the view of control performance of UAV, tri-level programing (TLP) model is designed to generate a smooth path. Then, the objective functions including the leader, middle-level follower and bottom-level follower function and decision variables of TLP are defined to guarantee the flight toward the target. In addition, the cognitive behavior optimization algorithm (COA) embedded with the proposed optimization strategies is used to solve this problem. Numerical experimental results and the comparison with PSO, RRT algorithm demonstrated the efficiency and effectiveness of the proposed approach.