An Improved NSGA-II Algorithm for UAV Path Planning Problems

Abstract

The path planning problem is an important research in the field of UAV application. In practical applications, the path planning problem is usually multi-objective. This paper proposes an improved NSGA-II algorithm to achieve multi-objective optimization path planning. The algorithm introduces an improved directional mutation strategy by adaptively adjusting the crossover probability and the mutation probability, and searches for the optimal path of the UAV under the premise of considering the path length, threat, and concealment. Simulation experiments show that, compared with the NSGA and NSGA-II algorithm, the improved NSGA-II algorithm can reduce the risk of falling into a local optimum, increase the convergence speed, and better realize path planning in an obstacle environment.