Development of a Product Recognition and Task Planning System for a Shelf-Stocking Robot

This paper describes the winning robot system in the WRS 2025 Future Convenience Store Challenge (WRS2025 FCSC), an international competition focused on tasks related to managing convenience store merchandise stock. To ensure reliable and efficient task execution, we enhanced the XYZ stage-type display system, which automates stock and disposal tasks. We introduced a two-stage recognition method that combines object detection using YOLO and identification using ArUco markers, enabling the high-precision acquisition of product type, position, and orientation. Furthermore, the work planning software was divided into three components: product management, task planning, and motion planning, improving program readability and debugging efficiency. Evaluation of the developed system at WRS2025 FCSC yielded the following results: in the preliminary round, it achieved a perfect score of 54 points in the Stock Task and 49 points in the Stock and Disposal Task. In the final round, it scored 54 points in the Stock Task and 31 points in the Stock and Disposal Task, securing the overall championship.