Research on path planning based on improved ant colony algorithm

Shicheng Wang; Zhian Zhang; Xuegong Huang

doi:10.1117/12.2671075

28 April 2023 Research on path planning based on improved ant colony algorithm

Shicheng Wang, Zhian Zhang, Xuegong Huang

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126105R (2023) https://doi.org/10.1117/12.2671075
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

Aiming at the problems of blindness, slow convergence and easy to fall into local optimal solution in the early stage of traditional ant colony algorithm search, an improved ant colony algorithm was proposed. The algorithm first introduces the gravitational potential field function, constructs new heuristic information, and improves the convergence speed. Secondly, learn from the wolf pack update rules, improve the pheromone update function, and give full play to the feedback function of pheromone. Finally, the path is optimized locally to remove redundant nodes. The comparison experiment with the traditional ant colony algorithm proves that the improved algorithm shortens the running time, the convergence speed and the global search ability are better than the traditional ant colony algorithm, and it is not easy to fall into the local optimal solution, which verifies the effectiveness of the algorithm.

Citation Download Citation

Shicheng Wang, Zhian Zhang, and Xuegong Huang "Research on path planning based on improved ant colony algorithm", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126105R (28 April 2023); https://doi.org/10.1117/12.2671075

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