Curvature-Based Continuous Steering of Stiffness-Dominant Concentric Tube Robots

Existing works on controlling a concentric tube robot (CTR) mostly focus on the trajectory of its tip position or pose. In order to safely send CTRs in a confined lumen space, we propose to continuously steer the CTRs so that its entire shape will always attempt to approximate target curves over time. We focus on stiffness-dominant CTRs. Considering the differential geometry of such CTR shapes, we propose to work on the curvature domain to reduce the computational cost in searching the configuration of the CTRs. With our formulation, we model the curvature control of the CTR to find the optimal translation of each tube and then search for the rotation of the tubes to fit the target shapes. We demonstrate our method using sets of different target paths. The computational time per frame, ranging between 0.1 to 0.3 seconds across all experiments, highlights the efficiency of our approach in aligning the complete shape of the CTR with specified paths. Notably, for time-varying trajectories that could be reproduced by the CTR with its maximum deployment length reaching 150 mm, the root mean square error and median error were 0.98mm and 0.46mm, respectively.

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Publication Details

Journal
IEEE Transactions on Automation Science and Engineering
Published
2025-01-01
DOI
https://doi.org/10.1109/tase.2025.3570861
Citations
1
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
0.67

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article

Curvature-Based Continuous Steering of Stiffness-Dominant Concentric Tube Robots

Lifeng Zhu, Aiguo Song, Xiaoliang Jin, Li-dan Xie
1 citations
IEEE Transactions on Automation Science and Engineering
Soft Robotics and Applications
0.67
article

Curvature-Based Continuous Steering of Stiffness-Dominant Concentric Tube Robots

Lifeng Zhu, Aiguo Song, Xiaoliang Jin, Li-dan Xie
article en
1 citations

Abstract

Existing works on controlling a concentric tube robot (CTR) mostly focus on the trajectory of its tip position or pose. In order to safely send CTRs in a confined lumen space, we propose to continuously steer the CTRs so that its entire shape will always attempt to approximate target curves over time. We focus on stiffness-dominant CTRs. Considering the differential geometry of such CTR shapes, we propose to work on the curvature domain to reduce the computational cost in searching the configuration of the CTRs. With our formulation, we model the curvature control of the CTR to find the optimal translation of each tube and then search for the rotation of the tubes to fit the target shapes. We demonstrate our method using sets of different target paths. The computational time per frame, ranging between 0.1 to 0.3 seconds across all experiments, highlights the efficiency of our approach in aligning the complete shape of the CTR with specified paths. Notably, for time-varying trajectories that could be reproduced by the CTR with its maximum deployment length reaching 150 mm, the root mean square error and median error were 0.98mm and 0.46mm, respectively.

IEEE Transactions on Automation Science and EngineeringVol. 22
State Key Laboratory of Digital Medical Engineering (CN), Southeast University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 32%
Soft Robotics and Applications
0.67
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