AGV Path Planning based on Improved Ant Colony Algorithm

Authors

  • Haoran Liu

DOI:

https://doi.org/10.54097/2cnrrd35

Keywords:

AGV, Ant Colony Algorithm, Path Optimization, Grid Map

Abstract

With the widespread application of Automated Guided Vehicles (AGV) in industrial production and warehouse logistics, the challenges they face during operation are becoming increasingly apparent. Currently, the path planning problem of AGV has become one of the hot topics in academic research. This paper provides an in-depth analysis of the performance of AGV in real-world scenarios and utilizes grid-based methods to construct a map environment model. Subsequently, a detailed analysis of the movement of AGV in the environment is conducted, and an improved pheromone method is proposed based on the traditional ant colony algorithm, aiming to optimize the navigation path of AGV to determine the optimal travel route.

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References

Liu Jiaqi, Wang Taihua, Dong Zheng. Mobile Robot Path Planning Based on Improved Ant Colony Algorithm[J]. Sensors and Microsystems, 2022, 41(5): 140-143.

Guo Shikai, Sun Xin. Mobile Robot Path Planning Based on Improved Particle Swarm Algorithm[J]. Electronic Measurement Technology, 2019, 42(3): 54-58.

Chen Hu, Song Zhichao, Guang Mengke, et al. Path Planning of Mobile Robots in Complex Environments[J]. Journal of Guangxi University (Natural Science Edition), 2021, 46(3): 692-702.

Gu Jun-hua,Fan Pei-pei,Song Qing-zeng.Improved culture ant colonyoptimization method for solving TSP problem.computer engineering andApplications[J].Computer Engineering and Applications,2010(26):49-52.

ROKBANI N,KUMAR R,ABRAHAM A,et al. Bi-heuristic ant colony optimization-based approaches for travelingsalesman problem [J].Soft Comput,2021,25(5):3775-3794.

Li Jun, Liu Guang-rui. Path planning of mobile robot based on improved ant colony algorithm[J].Machinery Design& Manufacture, 2010(8):164-165).

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Published

28-03-2024

Issue

Section

Articles

How to Cite

Liu, H. (2024). AGV Path Planning based on Improved Ant Colony Algorithm . Journal of Innovation and Development, 6(2), 42-46. https://doi.org/10.54097/2cnrrd35