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Automated hand eye calibration in laparoscope holding robot for robot assisted surgery
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Paper Abstract

In this paper, we describe an automated hand eye calibration in laparoscope holding robot for robot assisted surgery. In minimally invasive surgery, laparoscope holding robot can give more stability of the laparoscope images than human laparoscope assistants. We study on laparoscope holding robot controlled based on anatomical structure information during laparoscopic surgery. In order to operate laparoscope holding robot guided by images, it is necessary to make a vision system for laparoscope holding robot. We compute the position and orientation relationships between a laparoscope camera and a Tool Center Point (TCP) of robot arm to make a vision system. We utilize Tsai’s method for hand eye calibration to estimate the homogeneous transformation matrix between the TCP and laparoscope camera. We attached a laparoscope to an industrial robot arm. The robot arm is moved to different positions and captures calibration board images. Hand eye calibration is performed using recorded TCP positions and calibration board images. The homogeneous transformation matrices between the laparoscope camera coordinate and the laparoscope holding robot TCP coordinate is obtained by this hand eye calibration. The experimental result shown that the proposed method could compute the homogeneous transformation matrix between a laparoscope holding robot TCP and a laparoscope camera.

Paper Details

Date Published: 22 March 2019
PDF: 5 pages
Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 1104949 (22 March 2019); doi: 10.1117/12.2521618
Show Author Affiliations
Jiang Shuai, Nagoya Univ. (Japan)
Yuichiro Hayashi, Nagoya Univ. (Japan)
Cheng Wang, Nagoya Univ. (Japan)
Masahiro Oda, Nagoya Univ. (Japan)
Takayuki Kitasaka, Aichi Institute of Technology (Japan)
Kazunari Misawa, Aichi Cancer Ctr. Research Institute (Japan)
Kensaku Mori, Nagoya Univ. (Japan)
National Institute of Informatics (Japan)


Published in SPIE Proceedings Vol. 11049:
International Workshop on Advanced Image Technology (IWAIT) 2019
Qian Kemao; Kazuya Hayase; Phooi Yee Lau; Wen-Nung Lie; Yung-Lyul Lee; Sanun Srisuk; Lu Yu, Editor(s)

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