The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Shape Prediction Method for Electromagnet-Embedded Soft Catheter Robot

전자석 내장형 소프트 카테터 로봇 형상 예측 방법

  • Sanghyun Lee (Mechanical Engineering, Pusan National University, Hyundai Motor Company) ;
  • Donghoon Son (Mechanical Engineering, Pusan National University)
  • Received : 2023.10.25
  • Accepted : 2023.11.04
  • Published : 2024.02.29
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Abstract

This study introduces a novel method for predicting the shape of soft catheter robots embedded with electromagnets. As an advancement in the realm of soft robotics, these catheter robots are crafted from flexible and pliable materials, ensuring enhanced safety and adaptability during interactions with human tissues. Given the pivotal role of catheters in minimally invasive surgeries (MIS), our design stands out by facilitating active control over the orientation and intensity of the inbuilt electromagnets. This ensures precise targeting and manipulation of the catheter segments. The research encompasses a comprehensive breakdown of the magnetic modeling, tracking algorithms, experimental layout, and analytical techniques. Both simulation and experimental results validate the efficacy of our method, underscoring its potential to augment accuracy in MIS and revolutionize healthcare-oriented soft robotics.

Keywords

Acknowledgement

This work was supported by a 2-Year Research Grant of Pusan National University

References

  1. C. Lee, M. Kim, Y. J. Kim, N. Hong, S. Ryu, H. J. Kim, and S. Kim, "Soft robot review," International Journal of Control, Automation and Systems, vol. 15, pp. 3-15, Jan., 2017, DOI: 10.1007/s12555-016-0462-3. 
  2. A. Chen. R. Yin, L. Cao, C. Yuan, H. K. Ding, and W. J. Zhang, "Soft robotics: Definition and research issues," 2017 24th IEEE international conference on mechatronics and machine vision in practice (M2VIP), Auckland, New Zealand, pp. 366-370, 2017, DOI: 10.1109/M2VIP.2017.8267170. 
  3. D. Rus and M. T. Tolley, "Design, fabrication and control of soft robots," Nature, vol. 521, no. 7553, pp. 467-475, May, 2015, DOI: 10.1038/nature14543. 
  4. M. Cianchetti, C. Laschi, A. Menciassi, and P. Dario, "Biomedical applications of soft robotics," Nature Reviews Materials, vol. 3, no. 6, pp. 143-153, May, 2018, DOI: 10.1038/s41578-018-0022-y. 
  5. P. Polygerinos, Z. Wang, K. C. Galloway, R. J. Wood, and C. J. Walsh, "Soft robotic glove for combined assistance and at-home rehabilitation," Robotics and Autonomous Systems, vol. 73, pp. 135-143, Nov., 2015, DOI: 10.1016/j.robot.2014.08.014. 
  6. A. Ali, D. H. Plettenburg, and P. Breedveld, "Steerable catheters in cardiology: Classifying steerability and assessing future challenges," IEEE Transactions on Biomedical Engineering, vol. 63, no. 4, pp. 679-693, Apr., 2016, DOI: 10.1109/TBME.2016.2525785. 
  7. P. E. Dupont, J. Lock, B. Itkowitz, and E. Butler, "Design and control of concentric-tube robots," IEEE Transactions on Robotics, vol. 26, no. 2, pp. 209-225, Apr., 2010, DOI: 10.1109/TRO.2009.2035740. 
  8. F. Carpi and C. Pappone, "Stereotaxis Niobe® magnetic navigation system for endocardial catheter ablation and gastrointestinal capsule endoscopy," Expert review of medical devices, vol. 6, no. 5, pp. 487-498, Jan., 2014, DOI: 10.1586/erd.09.32. 
  9. Y. Kim, G. A. Parada, S. Liu, and X. Zhao, "Ferromagnetic soft continuum robots," Science Robotics, vol. 4, no. 33, Aug., 2019, DOI: 10.1126/scirobotics.aax7329. 
  10. Y. Haga, Y. Muyari, T. Mineta, T. Matsunaga, H. Akahori, and M. Esashi, "Small diameter hydraulic active bending catheter using laser processed super elastic alloy and silicone rubber tube," 2005 3rd IEEE/EMBS Special Topic Conference on Microtechnology in Medicine and Biology, Oahu, HI, USA, pp. 245-248, 2005, DOI: 10.1109/MMB.2005.1548439. 
  11. E. Ayvali, C.-P . Liang, M. Ho, Y. Chen, and J. P . Desai, "Towards a discretely actuated steerable cannula for diagnostic and therapeutic procedures," The International journal of robotics research, vol. 31, no. 5, pp. 588-603, Apr., 2012, DOI: 10.1177/0278364912442429.
  12. J. J. Abbott, E. Diller, and A. J. Petruska, "Magnetic Methods in Robotics," Annual Review of Control, Robotics, and Autonomous Systems, vol. 3, no. 1, pp. 57-90, May, 2020, DOI: 10.1146/annurev-control-081219-082713. 
  13. H. Yang, L. Shao, F. Zheng, L. Wang, and Z. Song, "Recent advances and trends in visual tracking: A review," Neurocomputing, vol. 74, no. 18, pp. 3823-3831, Nov., 2011, DOI: 10.1016/j.neucom.2011.07.024. 
  14. P. P. Gundewar and H. K. Abhyankar, "A review on an obstacle detection in navigation of visually impaired," International Organization of Scientific Research Journal of Engineering (IOSRJEN), vol. 3, no. 1, pp. 01-06, Jan., 2013, [online], http://iosrjen.org/Papers/vol3_issue1%20(part-2)/A03120106.pdf.  106.pdf
  15. L. Marechal, P. Balland, L. Lindenroth, F. Petrou, C. Kontovounisios, and F. Bello, "Toward a common framework and database of materials for soft robotics," Soft robotics, vol. 8, no. 3, pp. 284-297, Jun., 2021, DOI: 10.1089/soro.2019.0115.