Supervisor:
Southwest Ordnance Industry Bureau
Organizer:
Chongqing Ordnance Industry Society
Chongqing University of Technology
Chongqing University of Technology
UAV path planning based on improved sand cat swarm optimization algorithm
| DOI: | 10.11809/bqzbgcxb2025.03.022 |
| Keywords: | UAV; path planning; sand cat swarm optimization algorithm; triangle wandering strategy; levy flight strategy |
| Abstract: | To enhance the efficiency and accuracy of unmanned aerial vehicle’ (UAV) path planning in complex battlefield environments, a novel path planning algorithm based on the Sand Cat Swarm Optimization (SCSO) algorithm is proposed. The Iterative Chaotic Map is integrated into the population initialization to achieve a more uniformly distributed population. During the search and exploitation phases, the Triangle Wandering Strategy and Levy Flight Strategy are utilized, respectively, to extend the algorithm’s search range and precision. Furthermore, an elimination and updating mechanism is incorporated into the selection phase of the algorithm, leading to the development of the Modified Sand Cat Swarm Optimization (MSCSO) algorithm. Five comparative algorithms were selected, and the algorithm’s performance was tested using the CEC2022 test functions and Wilcoxon rank sum test. Several three dimensional simulation environments were constructed to conduct multiple sets of comparative simulations on path planning capabilities.The path planning capabilities in the simulation of a real environment was verified. The simulation results indicate that MSCSO possesses superior path planning capabilities. |
| Issue: | Vol. 46 No. 3 (2025) |
| Published: | 2025-03-31 |