MPC Design of a Continuum Robot for Pulmonary Interventional Surgery Using Koopman Operators

This letter focuses on the flexible tube of a bronchoscope robot used in pulmonary intervention surgery, which is considered as a continuum robot. The dynamics model is proposed based on the Koopman operator, leveraging real data to solve for the system matrix parameters accurately. To enhance control precision, we designed a model predictive control (MPC) algorithm aimed at tracking the desired curvature and deflection angles of the flexible tube. The MPC controller uses real-time data from electromagnetic sensors to adjust the tube shape, ensuring accurate and responsive manipulation. The effectiveness of the proposed algorithm are validated through extensive experiments conducted on the Binary experimental platform. Compared with the traditional open-loop control method, the proposed algorithm has achieved significant improvements in tracking performance and operational reliability. Each system state error of the proposed algorithm is smaller, which means that better tracking performance can be obtained under the proposed MPC scheme.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2024-10-17
DOI
https://doi.org/10.1109/lra.2024.3483048
Citations
4
Primary Topic
Gas Dynamics and Kinetic Theory
Type
article
Field-Weighted Citation Impact
3.90

Funders

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article

MPC Design of a Continuum Robot for Pulmonary Interventional Surgery Using Koopman Operators

Lifeng Zhu, Aiguo Song, Jiawei Deng, Jinfeng Li et al.
4 citations
IEEE Robotics and Automation Letters
Gas Dynamics and Kinetic Theory
3.90
article

MPC Design of a Continuum Robot for Pulmonary Interventional Surgery Using Koopman Operators

Lifeng Zhu, Aiguo Song, Jiawei Deng, Jinfeng Li, Yuhua Song, Cheng Wang
article en
4 citations

Abstract

This letter focuses on the flexible tube of a bronchoscope robot used in pulmonary intervention surgery, which is considered as a continuum robot. The dynamics model is proposed based on the Koopman operator, leveraging real data to solve for the system matrix parameters accurately. To enhance control precision, we designed a model predictive control (MPC) algorithm aimed at tracking the desired curvature and deflection angles of the flexible tube. The MPC controller uses real-time data from electromagnetic sensors to adjust the tube shape, ensuring accurate and responsive manipulation. The effectiveness of the proposed algorithm are validated through extensive experiments conducted on the Binary experimental platform. Compared with the traditional open-loop control method, the proposed algorithm has achieved significant improvements in tracking performance and operational reliability. Each system state error of the proposed algorithm is smaller, which means that better tracking performance can be obtained under the proposed MPC scheme.

IEEE Robotics and Automation LettersVol. 9(12)
State Key Laboratory of Digital Medical Engineering (CN), Southeast University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 6%
Gas Dynamics and Kinetic Theory
3.90
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