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作者:

Hao, Xiaolong (Hao, Xiaolong.) | Cheng, Qiang (Cheng, Qiang.) | Jia, Chengru (Jia, Chengru.) | Huang, He (Huang, He.) | Zhao, Shuai (Zhao, Shuai.) | Wang, Yi (Wang, Yi.)

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EI Scopus

摘要:

To ensure the high quality and stability of oral diagnosis and treatment images. It is required that the position of the X-ray ball tube is accurate during the shooting process. The artificial difference should be eliminated. In order to avoid cross infection between doctors and patients, an overall solution of intra-oral radiograph assisted robot (IRAR) was proposed, including face recognition, camera calibration, end effector spatial positioning and robot-oral interaction. The working environment and mechanism kinematics of IRAR were analyzed. Based on the establishment of binocular vision calibration system, a face recognition algorithm aided image method was proposed. The interaction model between virtual image and robot pose was analyzed. By analyzing the function of the robot end effector, the related parameter requirements of the end effector were established. Finally, the imaging work area planning scheme of the imaging robot was obtained. Through the interaction between the robot and the oral cavity, the non-contact dental medical images were photographed and disinfected. The repeated positioning accuracy of IRAR system shall not be greater than 1 mm. The average error is 0.5 mm. The experiment proved that IRAR can finish the shooting task smoothly and accurately. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词:

Diagnosis Machine design Stereo image processing Calibration Robot programming End effectors Medical imaging Binocular vision

作者机构:

  • [ 1 ] [Hao, Xiaolong]Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Hao, Xiaolong]Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Cheng, Qiang]Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Cheng, Qiang]Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Jia, Chengru]Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 6 ] [Huang, He]Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 7 ] [Huang, He]Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 8 ] [Zhao, Shuai]Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 9 ] [Zhao, Shuai]Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 10 ] [Wang, Yi]Department of Stomotology, General Hospital of the PLA, Beijing, China

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ISSN: 0302-9743

年份: 2022

卷: 13719 LNCS

页码: 48-58

语种: 英文

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