한국생산제조학회지 (Journal of the Korean Society of Manufacturing Technology Engineers)

  • 제25권6호
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  • Pages.522-531
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  • 2016
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  • 2508-5093(pISSN)
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  • 2508-5107(eISSN)
한국생산제조학회 (The Korean Society of Manufacturing Technology Engineers)
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빈-피킹을 위한 다관절 로봇 그리퍼의 관절 데이터를 이용한 물체 인식 기법

Method of Object Identification Using Joint Data of Multi-Joint Robotic Gripper for Bin-picking

  • Park, Jongwoo (Department of Robotics and Mechatronics, Korea Institute of Machinery and Materials) ;
  • Park, Chanhun (Department of Robotics and Mechatronics, Korea Institute of Machinery and Materials) ;
  • Park, Dong Il (Department of Robotics and Mechatronics, Korea Institute of Machinery and Materials) ;
  • Kim, DooHyung (Department of Robotics and Mechatronics, Korea Institute of Machinery and Materials)
  • 투고 : 2016.09.13
  • 심사 : 2016.12.01
  • 발행 : 2016.12.15
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초록

In this study, we propose an object identification method for bin-picking developed for industrial robots. We identify the grasp posture and the associated geometric parameters of grasp objects using the joint data of a robotic gripper. Prior to grasp identification, we analyze the grasping motion in a low-dimensional space using principle component analysis (PCA) to reduce the dimensions. We collected the joint data from a human hand to demonstrate the grasp-identification algorithm. For data acquisition of the human grasp data, we conducted additional research on the motion characteristics of a human hand. We explain the method for using the algorithm of grasp identification for bin-picking. Finally, we present a subject for future research using our proposed algorithm of grasp model and identification.

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참고문헌

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