| Title: | Study on scheduling and path planning problems of multi-AGVs based on a heuristic algorithm in intelligent manufacturing workshop |
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| Authors: | ID Wang, Y. J. (Author)
ID Liu, X.Q. (Author)
ID Leng, J. Y. (Author)
ID Wang, J. J. (Author)
ID Meng, Q. N. (Author)
ID Zhou, M. J. (Author) |
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| Files: |  APEM17-4_505-513.pdf (512,86 KB)
MD5: 64E08AE8122065050809496368B0E4D1
 https://apem-journal.org/Archives/2022/APEM17-4_505-513.pdf
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FS - Faculty of Mechanical Engineering
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| Abstract: | In order to solve the scheduling and path planning problems of multi-AGVs in an intelligent manufacturing workshop, it is necessary to consider loading, unloading, and transporting the workpiece of each AGV at the same time. A step task scheduling and path optimization mode of AGV is proposed. The process is as follows: Firstly, a mathematical model algorithm and a material transportation task allocation algorithm based on the urgency degree of workpiece processing were established for the optimization objective, and all workpiece transportation task sequences between shelves and processing equipment were assigned to the corresponding AGV to generate the initial feasible path of each AGV. Then, the AGV collision detection and anti-collision algorithm are designed to plan the global collision-free walking path of multi-AGVs in the workshop, and the path can be dynamically adjusted according to the delivery task. The model is solved by a heuristic algorithm ant colony algorithm and MATLAB coding. Finally, an example is given to verify the effectiveness of the method, which can effectively solve the task allocation of multi-AGVs and avoid collision path planning based on the transportation task sequence, and improve the work efficiency of AGV. This research can provide a theoretical basis and practical reference for realizing multi AGVs collaborative scheduling by using AGV automated material transport system in an intelligent production workshop. |
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| Keywords: | intelligent manufacturing, automated guided vehicle(AGV), multi-AGVs, task sequence, task scheduling, path planning, heuristic algorithm, ant colony algorithm, MATLAB |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 25.10.2022 |
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| Article acceptance date: | 17.12.2022 |
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| Publication date: | 30.12.2022 |
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| Publisher: | Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering |
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| Year of publishing: | 2022 |
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| Number of pages: | str. 505-513 |
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| Numbering: | Vol. 17, no. 4 |
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| PID: | 20.500.12556/DKUM-97230  |
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| UDC: | 681.5:004.023 |
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| ISSN on article: | 1854-6250 |
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| COBISS.SI-ID: | 269454851 |
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| DOI: | 10.14743/apem2022.4.452 |
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| Copyright: | Content from this work may be used under the terms of the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. |
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| Publication date in DKUM: | 24.02.2026 |
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| Views: | 183 |
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| Downloads: | 1 |
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| Metadata: |    |
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| Categories: | Misc.
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