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Closed-loop control of bevel-tip needles based on path planning

Published online by Cambridge University Press:  24 August 2018

Benyan Huo Open the ORCID record for Benyan Huo [Opens in a new window] ,
Xingang Zhao ,
Jianda Han  and
Weiliang Xu
Benyan Huo*
Affiliation:
School of electrical engineering, Zhengzhou University, Zhengzhou, P.R. China Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang, P.R. China. Emails: zhaoxingang@sia.cn, jdhan@sia.cn
Xingang Zhao
Affiliation:
Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang, P.R. China. Emails: zhaoxingang@sia.cn, jdhan@sia.cn
Jianda Han
Affiliation:
Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang, P.R. China. Emails: zhaoxingang@sia.cn, jdhan@sia.cn
Weiliang Xu
Affiliation:
University of Auckland, Auckland, New Zealand. Email: p.xu@auckland.ac.nz
*
*Corresponding author. E-mail: huoby@zzu.edu.cn
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Summary

Bevel-tip needles have the potential to improve paracentetic precision and decrease paracentetic traumas. In order to drive bevel-tip needles precisely with the constrains of path length and path dangerousness, we propose a closed-loop control method that only requires the position of the needle tip and can be easily applied in a clinical setting. The control method is based on the path planning method proposed in this paper. To establish the closed-loop control method, a kinematic model of bevel-tip needles is first presented, and the relationship between the puncture path and controlled variables is established. Second, we transform the path planning method into a multi-objective optimization problem, which takes the path error, path length and path dangerousness into account. Multi-objective particle swarm optimization is employed to solve the optimization problem. Then, a control method based on path planning is presented. The current needle tip attitude is essential to plan an insertion path. We analyze two methods to obtain the tip attitude and compare their effects using both simulations and experiments. In the end, simulations and experiments in phantom tissue are executed and analyzed, the results show that our methods have high accuracy and have the ability to deal with the model parameter uncertainty.

Keywords

Medical roboticsBevel-tip needleParticle swarm optimizationPath planningUKF
Type
Articles
Information
Robotica , Volume 36 , Issue 12 , December 2018 , pp. 1857 - 1873
Copyright
Copyright © Cambridge University Press 2018 

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