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On-Demand Multi-Agent Basket Picking for Shopping Stores
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-8546-4431
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-9240-4605
Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering.
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2023 (English)In: 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023Conference paper, Published paper (Refereed)
Abstract [en]

Imagine placing an online order on your way to the grocery store, then being able to pick the collected basket upon arrival or shortly after. Likewise, imagine placing any online retail order, made ready for pickup in minutes instead of days. In order to realize such a low-latency automatic warehouse logistics system, solvers must be made to be basketaware. That is, it is more important that the full order (the basket) is picked timely and fast, than that any single item  in the order is picked quickly. Current state-of-the-art methods are not basket-aware. Nor are they optimized for a positive customer experience, that is; to prioritize customers based on queue place and the difficulty associated with  picking their order. An example of the latter is that it is preferable to prioritize a customer ordering a pack of diapers over a customer shopping a larger order, but only as long as the second customer has not already been waiting for  too long. In this work we formalize the problem outlined, propose a new method that significantly outperforms the state-of-the-art, and present a new realistic simulated benchmark. The proposed method is demonstrated to work in an on-line and real-time setting, and to solve the on-demand multi-agent basket picking problem for automated shopping stores under realistic conditions.

Place, publisher, year, edition, pages
2023.
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-195381OAI: oai:DiVA.org:liu-195381DiVA, id: diva2:1770277
Conference
International Conference on Robotics and Automation (ICRA), London, 29 May - 2 June 2023
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)Knut and Alice Wallenberg Foundation, KAW 2019.0350ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsCUGS (National Graduate School in Computer Science)EU, Horizon 2020, GA No 952215Available from: 2023-06-19 Created: 2023-06-19 Last updated: 2023-06-28Bibliographically approved

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Tiger, MattiasBergström, DavidHeintz, Fredrik

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Tiger, MattiasBergström, DavidWijk Stranius, SimonHolmgren, Evelinade Leng, DanielHeintz, Fredrik
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Artificial Intelligence and Integrated Computer SystemsFaculty of Science & EngineeringDepartment of Computer and Information Science
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