UAV path planning based on improved ant colony algorithm with multiple heuristic factors

Wentao Li; Xin Chen

doi:10.1117/12.2645100

30 August 2022 UAV path planning based on improved ant colony algorithm with multiple heuristic factors

Wentao Li, Xin Chen

Proceedings Volume 12309, International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2022); 123092Z (2022) https://doi.org/10.1117/12.2645100
Event: International Conference on Advanced Manufacturing Technology and Manufacturing System (ICAMTMS 2022), 2022, Shijiazhuang, China

Abstract

Aiming at the problems of long search time and easy to fall into deadlock when using the traditional ant colony algorithm in the path planning process of UAV in two-dimensional space, this paper first introduces the advantages and disadvantages of the traditional algorithm, and puts forward an improved ant colony algorithm. Select A*, potential field method, traditional heuristic search strategy and obstacle avoidance heuristic search, improve pheromone update algorithm, and dynamically modify the dependence of transition probability on pheromone. The simulation results show that the improved ant colony algorithm has better global search ability, the path superiority is more prominent, the number of iterations and calculation time are optimized, and the stability of path search is greatly improved.

Citation Download Citation

Wentao Li and Xin Chen "UAV path planning based on improved ant colony algorithm with multiple heuristic factors", Proc. SPIE 12309, International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2022), 123092Z (30 August 2022); https://doi.org/10.1117/12.2645100

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