Urban UAV Path Planning Based on Improved Beetle Search Algorithm

Authors

Qingqing Yang, School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China; Yunnan Provincial Key Laboratory of Computer Science, Kunming University of Science and Technology, Kunming 650500, ChinaFollow
Minyi Deng, School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China; Yunnan Provincial Key Laboratory of Computer Science, Kunming University of Science and Technology, Kunming 650500, China
Yi Peng, School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China; Yunnan Provincial Key Laboratory of Computer Science, Kunming University of Science and Technology, Kunming 650500, ChinaFollow

Abstract

Abstract: An improved SABAS is proposed to improve the safety and path smoothing of UAV missions in urban multi-obstacle environments and to obtain the shortest path. The algorithm no longer completely depends on the difference of odor concentration between the left and the right tentacles of beetle when exploring the path for position update. Instead, it makes full use of the strong searching ability of BAS algorithm, and introduces the annealing algorithm to add the neighborhood position solution of the next position, and finally selects the next best position from the neighborhood position solution. Metropolis criterion of annealing algorithm is used to judge whether the obtained best position is mobile or not, which overcomes the shortcoming of classical BAS being easy to fall into local optimal solution. Simulation results show that SABAS is superior to BAS and ACO convergence speed, safety, smoothness and the length of the path in urban multi-obstacle environment. It can be concluded that the planned path is optimal when the initial step size and step size factor are 16 m and 0.99 respectively in the current multi-obstacle city scenario.

Recommended Citation

Yang, Qingqing; Deng, Minyi; and Peng, Yi (2023) "Urban UAV Path Planning Based on Improved Beetle Search Algorithm," Journal of System Simulation: Vol. 35: Iss. 12, Article 3.
DOI: 10.16182/j.issn1004731x.joss.22-0778
Available at: https://dc-china-simulation.researchcommons.org/journal/vol35/iss12/3

First Page

2527

Last Page

2536

CLC

TP391.9

Recommended Citation

Yang Qingqing, Deng Minyi, Peng Yi. Urban UAV Path Planning Based on Improved Beetle Search Algorithm[J]. Journal of System Simulation, 2023, 35(12): 2527-2536.

Corresponding Author

Peng Yi

DOI

10.16182/j.issn1004731x.joss.22-0778