Direct Multi-Target Teaching Interface for Autonomous Handling of Multi-Stack Logistics in a Warehouse

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Abstract
This study presents a framework for enabling autonomous pick–place operations, addressing the need for efficiency in complex logistics environments using a direct multi-target teaching interface. First, tag and segmentation information were combined to recognize products in a complex warehouse, and a camera was installed on the rack to allow workers to remotely see the work environment, allowing workers to view the work environment in real time through a tablet. Workers can access the camera view showing the rack containing the target product through a swiping action and select the target product through direct teaching action. When the target product is finally selected, an optimal path is created through task planning, and an autonomous pick–place operation is performed based on the generated path. As a result of conducting a usability evaluation using the SUS (System Usability Scale) with six users on the interface that enables these tasks, it was confirmed that high user satisfaction was achieved with an average of 77.5 points. In conclusion, the proposed interface enhances operational efficiency and provides a user-friendly solution for complex warehouse tasks.
Funding Information
  • Soongsil University Research Fund (Convergence Research) (IITP-2024-RS-2022-00156360)
  • Korea government (IITP-2024-RS-2022-00156360)

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