Ultrasound-guided prostate percutaneous intervention robot system and calibration by informative particle swarm optimization

Jiawen YAN, Bo PAN, Yili FU

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Front. Mech. Eng. ›› 2022, Vol. 17 ›› Issue (1) : 3. DOI: 10.1007/s11465-021-0659-x
RESEARCH ARTICLE
RESEARCH ARTICLE

Ultrasound-guided prostate percutaneous intervention robot system and calibration by informative particle swarm optimization

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Abstract

Applying a robot system in ultrasound-guided percutaneous intervention is an effective approach for prostate cancer diagnosis and treatment. The limited space for robot manipulation restricts structure volume and motion. In this paper, an 8-degree-of-freedom robot system is proposed for ultrasound probe manipulation, needle positioning, and needle insertion. A novel parallel structure is employed in the robot system for space saving, structural rigidity, and collision avoidance. The particle swarm optimization method based on informative value is proposed for kinematic parameter identification to calibrate the parallel structure accurately. The method identifies parameters in the modified kinematic model stepwise according to parameter discernibility. Verification experiments prove that the robot system can realize motions needed in targeting. By applying the calibration method, a reasonable, reliable forward kinematic model is built, and the average errors can be limited to 0.963 and 1.846 mm for insertion point and target point, respectively.

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Keywords

ultrasound image guidance / prostate percutaneous intervention / parallel robot / kinematics identification / particle swarm optimization / informative value

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Jiawen YAN, Bo PAN, Yili FU. Ultrasound-guided prostate percutaneous intervention robot system and calibration by informative particle swarm optimization. Front. Mech. Eng., 2022, 17(1): 3 https://doi.org/10.1007/s11465-021-0659-x

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Acknowledgements

This paper was supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 51521003), the National Natural Science Foundation of China (Grant No. 61803341), and the Self-Planned Task of State Key Laboratory of Robotics and System (Harbin Institute of Technology, China) (Grant No. SKLRS202009B). No conflicts of interest exist in this paper.

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2022 The Author(s) 2022. This article is published with open access at link.springer.com and journal.hep.com.cn.
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