The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Development of Collaborative Dual Manipulator System for Packaging Industrial Coils

산업용 코일 포장을 위한 협동 양팔 로봇 시스템의 개발

  • Haeseong Lee (Department of Intelligence and Information, Graduate School of Convergence Science and Technology, Seoul National University) ;
  • Yonghee Lee (Interdisciplinary Program in Artificial Intelligence, Seoul National University) ;
  • Jaeheung Park (Graduate School of Convergence Science and Technology, ASRI, RICS, Seoul National University, Korea and Advanced Institutes of Convergence Technology)
  • 이해성 ;
  • 이용희 ;
  • 박재흥
  • Received : 2024.02.14
  • Accepted : 2024.05.13
  • Published : 2024.08.30
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Abstract

This paper introduces a dual manipulator system designed to automate the packaging process of industrial coils, which exhibit higher variability than other structured industrial fields due to diverse commercial requirements. The conventional solution involves the direct-teaching method, where an operator instructs the robot on a target configuration. However, this method has distinct limitations, such as low flexibility in dealing with varied sizes and safety concerns for the operators handling large products. In this sense, this paper proposes a two-step approach for coil packaging: motion planning and assembly execution. The motion planning includes a Rapidly-exploring Random Tree algorithm and a smoothing method, allowing the robot to reach the target configuration. In the assembly execution, the packaging is considered a peg-in-hole assembly. Unlike typical peg-in-hole assembly handling two workpieces, the packaging includes three workpieces (e.g., coil, inner ring, side plate). To address this assembly, the paper suggests a suitable strategy for dual manipulation. Finally, the validity of the proposed system is demonstrated through experiments with three different sizes of coils, replicating real-world packaging situations.

Keywords

Acknowledgement

This work was funded by POSCO and partly supported by IITP grant funded by the Korea government [NO.2021-0-01343, Artificial Intelligence Graduate School Program (Seoul National University)].

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