Ant colony algorithm in the application of path planning research

Xinyi Shu; Shuxi Chen; Yiyang Sun; Li Zhang

doi:10.1117/12.3051418

18 November 2024 Ant colony algorithm in the application of path planning research

Xinyi Shu, Shuxi Chen, Yiyang Sun, Li Zhang

Proceedings Volume 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) ; 134030C (2024) https://doi.org/10.1117/12.3051418
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, 2024, Zhengzhou, China

Abstract

With the rapid development of artificial intelligence and optimization algorithms, the Ant Colony Optimization (ACO) has become one of the effective tools for solving path planning problems. This paper first introduces the basic principles and key concepts of the ant colony algorithm, and then elaborates on its application in path planning problems in detail. Several comparative experiments are conducted to demonstrate the advantages and limitations of the ant colony algorithm in solving path planning problems. The performance of the ant colony algorithm is verified through experiments, and its potential in practical applications is discussed.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xinyi Shu, Shuxi Chen, Yiyang Sun, and Li Zhang "Ant colony algorithm in the application of path planning research", Proc. SPIE 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) , 134030C (18 November 2024); https://doi.org/10.1117/12.3051418

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