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Demo Abstract: Collaborative Real-Time Scheduling (CRTS) Algorithm for AGV Transportation System within a CPS Architecture

Published: 09 May 2023 Publication History

Abstract

The use of Autonomous Guided Vehicles (AGVs) is important in smart factories to enhance manufacturing operations. However, current AGV scheduling algorithms are inadequate and not connected to real-time data on manufacturing needs, leading to underutilized AGVs and missed delivery deadlines. The lack of algorithms that ensure timely delivery of materials results in idle time of AGVs and material shortages. We present a collaborative real-time scheduling (CRTS) algorithm for AGVs in smart factories. The algorithm not only ensures timely delivery of materials to processing units but also predicts the minimum number of AGVs required. The algorithm is designed to operate within a cyber-physical system architecture, where AGVs and processing units exchange data via a wireless network. The simulation results on the Node-Red platform show that the algorithm is efficient and adequate to meet real-time delivery requirements, with an average AGV utilization of over 92%.

References

[1]
[1] Tang, Gang, et al. "Geometric A-star algorithm: An improved A-star algorithm for AGV path planning in a port environment." IEEE access 9 (2021): 59196-59210.
[2]
[2] Yap, Yee Yang, and Bee Ee Khoo. "Landmark-based automated guided vehicle localization algorithm for warehouse application." Proceedings of the 2019 2nd International Conference on Electronics and Electrical Engineering Technology. 2019.
[3]
[3] Yao, Fengjia, et al. "Optimizing the scheduling of autonomous guided vehicle in a manufacturing process." 2018 IEEE 16th International Conference on Industrial Informatics (INDIN). IEEE, 2018.

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  1. Demo Abstract: Collaborative Real-Time Scheduling (CRTS) Algorithm for AGV Transportation System within a CPS Architecture

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          cover image ACM Conferences
          IoTDI '23: Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation
          May 2023
          514 pages
          ISBN:9798400700378
          DOI:10.1145/3576842
          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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          Published: 09 May 2023

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