Research on AGV Intelligent Parking Navigation Path Planning Based on A* Algorithm
Pages 579 - 585
Abstract
In this paper, for the AGV navigation path planning algorithm design problems, explored and researched the idea and implementation process of the A* algorithm, constructed the experimental environment model of AGV navigation path planning by using grid graphs, and carried out experiments with the help of simulation tools to verify the impact of different neighborhood node expansion search methods on the path planning speed in the A* algorithm. From the experimental data comparison and analysis results, it is concluded that the node expansion search method plays a key role in the efficiency of path planning. The results of the exploration research will provide a certain reference basis for the correct selection of node neighborhood expansion search method for AGV navigation route path planning in the actual production environment.
References
[1]
GUO Chao, CHEN Xiangling, GUO Peng Conflict-free path planning for multiple AGVs based on spatio-temporal A∼* algorithm [J]. Computer System Applications, 2022, 31(04): 360-368.
[2]
ZHANG Yuan, CHEN Yuxuan, WEI Lulu. AGV intelligent parking algorithm based on improved A∼* algorithm [J]. Computer System Applications, 2019, 28(01): 216-221.
[3]
ZHAO Xiao, WANG Zheng, HUANG Chengkan Mobile robot path planning based on improved A* algorithm [J]. Robotics, 2018, 40(06): 903-910.
[4]
Pang YX, Yuan DC. Fusion of improved A∼* and DWA algorithms for mobile robot path planning [J]. Computer and Modernization, 2022, (01):103-107.
[5]
SHEN Keyu, YU Zhiyu, LIU Yongxin Mobile robot path planning based on improved A∼* algorithm [J]. Computer Application Research, 2023, 40(01): 75-79.
[6]
MA Fei, YANG Haodong, GU Qing Navigation path planning for underground unmanned scraper based on improved A* algorithm [J]. Journal of Agricultural Machinery, 2015, 46(07):303-309.
[7]
CHEN Jiabao, WEN Jiayan, XIE Guangming. Mobile robot path planning based on improved A∼* algorithm [J]. Journal of Guangxi University of Science and Technology, 2022, 33(01): 78-84.
[8]
Application of Reverse Car-seeking in Large Underground Parking Lot Based on A Star Algorithm: A Real Case [J]. Lingxiang Wei; Dong Pan; Mingjun Liao. Scientific Research and Reviews, 2020.
[9]
Trajectory Tracking Design for a Swarm of Autonomous Mobile Robots: A Nonlinear Adaptive Optimal Approach [J]. Chen YungHsiang; Chen YungYue. Mathematics, 2022, (20).
[10]
WANG Si-Xin, TAN Gong-Quan,JIANG Qin Mobile robot path planning based on improved A∼* algorithm [J]. Computer Simulation, 2021, 38(09): 386-389+404.
[11]
SHEN Rui, LIU Jia, WANG Mengyuan Improved A∼* algorithm for mobile robot path planning design [J]. Journal of Tianjin Vocational and Technical Normal University, 2022, 32(01): 14-19.
[12]
A Voronoi-diagram-based dynamic path-planning system for underactuated marine vessels [J]. Mauro Candeloro; Anastasios M. Lekkas; Asgeir J. Sørensen. Control Engineering Practice, 2017.
[13]
The A* Algorithm for Path Planning Paul's Pub, Jan 24, 2019, https://paul.pub/a-star-algorithm/.
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Published In
October 2023
1809 pages
ISBN:9798400708305
DOI:10.1145/3650400
Copyright © 2023 ACM.
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Association for Computing Machinery
New York, NY, United States
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Published: 17 April 2024
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- Research-article
- Research
- Refereed limited
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- Research on the application of intelligent parking guidance system based on edge computing
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EITCE 2023
EITCE 2023: 2023 7th International Conference on Electronic Information Technology and Computer Engineering
October 20 - 22, 2023
Xiamen, China
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Overall Acceptance Rate 508 of 972 submissions, 52%
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