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Zhang T, Li G, Yang X, Ren H, Guo D, Wang H, Chan K, Ye Z, Zhao T, Zhang C, Shang W, Shen Y. A Fast Soft Continuum Catheter Robot Manufacturing Strategy Based on Heterogeneous Modular Magnetic Units. Micromachines (Basel) 2023; 14:mi14050911. [PMID: 37241535 DOI: 10.3390/mi14050911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 04/18/2023] [Accepted: 04/21/2023] [Indexed: 05/28/2023]
Abstract
Developing small-scale continuum catheter robots with inherent soft bodies and high adaptability to different environments holds great promise for biomedical engineering applications. However, current reports indicate that these robots meet challenges when it comes to quick and flexible fabrication with simpler processing components. Herein, we report a millimeter-scale magnetic-polymer-based modular continuum catheter robot (MMCCR) that is capable of performing multifarious bending through a fast and general modular fabrication strategy. By preprogramming the magnetization directions of two types of simple magnetic units, the assembled MMCCR with three discrete magnetic sections could be transformed from a single curvature pose with a large tender angle to a multicurvature S shape in the applied magnetic field. Through static and dynamic deformation analyses for MMCCRs, high adaptability to varied confined spaces can be predicted. By employing a bronchial tree phantom, the proposed MMCCRs demonstrated their capability to adaptively access different channels, even those with challenging geometries that require large bending angles and unique S-shaped contours. The proposed MMCCRs and the fabrication strategy shine new light on the design and development of magnetic continuum robots with versatile deformation styles, which would further enrich broad potential applications in biomedical engineering.
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Affiliation(s)
- Tieshan Zhang
- The Robot and Automation Center and the Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong 999077, China
- Shenzhen Research Institute, City University of Hong Kong, Shenzhen 518057, China
- The Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong 999077, China
| | - Gen Li
- The Robot and Automation Center and the Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong 999077, China
- Shenzhen Research Institute, City University of Hong Kong, Shenzhen 518057, China
- The Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong 999077, China
| | - Xiong Yang
- The Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong 999077, China
- Research Center on Smart Manufacturing, Hong Kong University of Science and Technology, Kowloon, Hong Kong 999077, China
| | - Hao Ren
- The Robot and Automation Center and the Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong 999077, China
- Shenzhen Research Institute, City University of Hong Kong, Shenzhen 518057, China
| | - Dong Guo
- The Robot and Automation Center and the Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong 999077, China
- Shenzhen Research Institute, City University of Hong Kong, Shenzhen 518057, China
| | - Hong Wang
- The Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong 999077, China
- Research Center on Smart Manufacturing, Hong Kong University of Science and Technology, Kowloon, Hong Kong 999077, China
| | - Ki Chan
- Prince Philip Dental Hospital, Faculty of Dentistry, University of Hong Kong, Hong Kong 999077, China
| | - Zhou Ye
- Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, University of Hong Kong, Hong Kong 999077, China
| | - Tianshuo Zhao
- The Department of Electrical and Electronic Engineering, University of Hong Kong, Hong Kong 999077, China
| | - Chengfei Zhang
- Prince Philip Dental Hospital, Faculty of Dentistry, University of Hong Kong, Hong Kong 999077, China
| | - Wanfeng Shang
- Guangdong Provincial Key Laboratory of Robotics and Intelligent System, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Yajing Shen
- The Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong 999077, China
- Research Center on Smart Manufacturing, Hong Kong University of Science and Technology, Kowloon, Hong Kong 999077, China
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