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Accurate Pose Measurement of Label-attached Small Objects Using a 3D Vision Technique

3차원 비전 기술을 이용한 라벨부착 소형 물체의 정밀 자세 측정

  • Kim, Eung-su (School of Computer Science and Engineering, Kyungpook National University) ;
  • Kim, Kye-Kyung (Intelligent Cognitive Technology Research Department, ETRI) ;
  • Wijenayake, Udaya (School of Computer Science and Engineering, Kyungpook National University) ;
  • Park, Soon-Yong (School of Computer Science and Engineering, Kyungpook National University)
  • 김응수 (경북대학교 IT대학 컴퓨터학부) ;
  • 김계경 (한국전자통신연구원 지능형인지기술연구부) ;
  • ;
  • 박순용 (경북대학교 IT대학 컴퓨터학부)
  • Received : 2016.07.26
  • Accepted : 2016.09.20
  • Published : 2016.10.01

Abstract

Bin picking is a task of picking a small object from a bin. For accurate bin picking, the 3D pose information, position, and orientation of a small object is required because the object is mixed with other objects of the same type in the bin. Using this 3D pose information, a robotic gripper can pick an object using exact distance and orientation measurements. In this paper, we propose a 3D vision technique for accurate measurement of 3D position and orientation of small objects, on which a paper label is stuck to the surface. We use a maximally stable extremal regions (MSERs) algorithm to detect the label areas in a left bin image acquired from a stereo camera. In each label area, image features are detected and their correlation with a right image is determined by a stereo vision technique. Then, the 3D position and orientation of the objects are measured accurately using a transformation from the camera coordinate system to the new label coordinate system. For stable measurement during a bin picking task, the pose information is filtered by averaging at fixed time intervals. Our experimental results indicate that the proposed technique yields pose accuracy between 0.4~0.5mm in positional measurements and $0.2-0.6^{\circ}$ in angle measurements.

Acknowledgement

Grant : 인지기반 제어기술개발 및 다중로봇 협업생산공정 적용 기술 개발

Supported by : 한국산업기술평가관리원, 한국연구재단

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