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JRM Vol.36 No.6 pp. 1527-1536
doi: 10.20965/jrm.2024.p1527
(2024)

Paper:

Development of Automated Display Shelf System for New Purchasing Experience by Dynamic Product Layout Changes

Masashi Seki* ORCID Icon, Kazuyoshi Wada* ORCID Icon, and Tetsuo Tomizawa**

*Graduate School of Systems Design, Department of Mechanical Systems Engineering, Tokyo Metropolitan University
6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan

**Department of Mechanical Engineering, National Institute of Technology, Tokyo College
1220-2 Kunugida-machi, Hachioji, Tokyo 193-0997, Japan

Received:
May 30, 2024
Accepted:
September 11, 2024
Published:
December 20, 2024
Keywords:
product stocking robot, automated display shelf, convenience store, product layout, planogram
Abstract

This study proposes a micro-logistics node as a new infrastructure envisioned for future convenience stores. This system automates the management of products on shelves, reduces the workload on store clerks, and provides an entirely new shopping experience with optimal displays based on the time and customers visiting the store. Automated warehouse technology has recently advanced, and the storage and removal of items from warehouse racks have been successfully automated. However, when considering implementation in convenience stores, robotic systems must adapt to their unique conditions: operation in limited backyard space, handling a wide variety of products with different sizes and shapes, and minimization of dead space in product displays. To address these challenges, this study developed a robot system that travels on vertical and horizontal tracks installed behind display shelves, and places products stored in special trays at any coordinate on the shelves.

Automated display shelf for dynamic layouts

Automated display shelf for dynamic layouts

Cite this article as:
M. Seki, K. Wada, and T. Tomizawa, “Development of Automated Display Shelf System for New Purchasing Experience by Dynamic Product Layout Changes,” J. Robot. Mechatron., Vol.36 No.6, pp. 1527-1536, 2024.
Data files:
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Last updated on Jan. 08, 2025