Paper
10 August 2023 A path planning method for mobile robots incorporating artificial potential field method and ant colony algorithm
Yi Xu, QiBing Jin, Yang Zhang
Author Affiliations +
Proceedings Volume 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023); 127591F (2023) https://doi.org/10.1117/12.2686536
Event: 2023 3rd International Conference on Automation Control, Algorithm and Intelligent Bionics (ACAIB 2023), 2023, Xiamen, China
Abstract
For the problems of long planning paths and slow convergence speed of the ant colony optimization (ACO) in mobile robot path planning, this paper improves the ant colony optimization and introduces the artificial potential field method (APF). Firstly, the initial pheromone concentration is differentiated to make the ants more directional at the early stage of the algorithm. Second, the heuristic factor in the heuristic function is dynamically adjusted to optimize the pheromone update strategy so that the algorithm can effectively distinguish the high-quality paths from the common ones. Finally, the distance parameter is added to the repulsion function of APF, the improved ant colony algorithm is fused with APF, and a fusion algorithm based on the improved ant colony algorithm-artificial potential field method (IACO-APF) is proposed. In the simulation experiments, the trajectories are optimized by the B-spline curve method, and the experiments show that the IACO-APF algorithm can obtain better solutions in a shorter time compared with the traditional ant colony algorithm and other algorithms mentioned in the literature.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yi Xu, QiBing Jin, and Yang Zhang "A path planning method for mobile robots incorporating artificial potential field method and ant colony algorithm", Proc. SPIE 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023), 127591F (10 August 2023); https://doi.org/10.1117/12.2686536
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KEYWORDS
Detection and tracking algorithms

Mathematical optimization

Computer simulations

Mobile robots

Polonium

Raster graphics

MATLAB

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