Research on UAV Smooth Path Planning Method Based on Improved Ant Lion Algorithm

UAV path planning is a key part of UAV's realization of intelligence. In the actual three-dimensional flight environment, it will be subject to many constraints, including the influence of terrain and obstacles and the constraints of the flight dynamics of the aircraft itself. In addition, the...

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Bibliographic Details
Published in2021 International Conference on Intelligent Computing, Automation and Applications (ICAA) pp. 180 - 189
Main Authors Wang, Hao, Gong, Huajun, Wang, Xinhua, Liang, Huan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2021
Subjects
Aircraft
Automation
Heuristic algorithms
Path planning
Search problems
Simulation
Splines (mathematics)
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Summary:UAV path planning is a key part of UAV's realization of intelligence. In the actual three-dimensional flight environment, it will be subject to many constraints, including the influence of terrain and obstacles and the constraints of the flight dynamics of the aircraft itself. In addition, the three-dimensional environment is more complicated than the two-dimensional environment. The traditional ALO algorithm is not satisfactory in the three-dimensional path planning, and it has defects in both the optimization efficiency and the optimization ability. In response to these problems, firstly, a dynamic convergence adaptive weight (DCAW) factor is proposed to improve the Antlion position update method, so that the explored path can maintain the optimal path; secondly, in order to reduce the amount of calculation, a chaotic search is proposed to replace the random walk of ants; finally introducing the B-spline curve smooth path design theory to smooth the optimized path can obtain a smooth and optimal path suitable for UAV flight. And the simulation results prove the feasibility and superiority of the improved algorithm.
DOI:10.1109/ICAA53760.2021.00039