UAV Path Planning in Complex Environments and Its Improved Artificial Rabbits Optimization Algorithm

Authors

Anlin Yin, Guizhou Provincial Characteristic Key Laboratory of System Optimization and Scientific Computation, College of Big Data and Information Engineering, Guizhou University, Guiyang 550025, China
Zhuhong Zhang, Guizhou Provincial Characteristic Key Laboratory of System Optimization and Scientific Computation, College of Big Data and Information Engineering, Guizhou University, Guiyang 550025, China

Abstract

Abstract: The work probes into the model design of reliable and effective UAV path planning in complex obstacle environments and its related optimization algorithm. In the model design, a weight coefficient method and cylindrical coordinate system-based single-objective path planning model is developed to solve the UAV's flight path, in which the distance, angle, height and threat cost are taken as performance indices and obstacles in the ground and spatial regions are regarded as constraints. In the algorithm design, the SPM chaotic mapping is used to improve the initial population distribution of the artificial rabbit optimization algorithm in view of the problems of uneven distribution of the initial population, the imbalance between exploration and exploitation capacities and the insufficient local search capacity. The local search ability is enhanced by the elite individual guidance strategy. An improved artificial rabbits optimization algorithm with computational complexity determined by population size is proposed to solve large-scale optimization problems. The comparative experiments have validated that, the path planning model is available and can alleviate the influence of the increasing number of track points to the quality of the path planning scheme, and at the same time the improved algorithm can effectively handle high-dimensional optimization problems and is of potential value for the UAV path planning problem.

Recommended Citation

Yin, Anlin and Zhang, Zhuhong (2025) "UAV Path Planning in Complex Environments and Its Improved Artificial Rabbits Optimization Algorithm," Journal of System Simulation: Vol. 37: Iss. 1, Article 7.
DOI: 10.16182/j.issn1004731x.joss.23-1103
Available at: https://dc-china-simulation.researchcommons.org/journal/vol37/iss1/7

First Page

79

Last Page

94

CLC

TP391.9

Recommended Citation

Yin Anlin, Zhang Zhuhong. UAV Path Planning in Complex Environments and Its Improved Artificial Rabbits Optimization Algorithm[J]. Journal of System Simulation, 2025, 37(1): 79-94.

Corresponding Author

Zhang Zhuhong

DOI

10.16182/j.issn1004731x.joss.23-1103