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FBG-based 3D shape sensor based on spun multi-core fibre for continuum surgical robots

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Abstract

The advance of minimally invasive interventional surgeries has accelerated the iterative upgrading of continuum surgical robots. High compatibility with robotic applications and high precision are key features of sensors for robot navigation. In this paper, a spun multi-core fibre (SMCF) 3D shape sensor for continuum surgical robots is proposed. The sensor is fabricated by ultraviolet (UV) light inscribing fibre Bragg gratings (FBGs) in the SMCF, showing good spectra characteristics. Shape reconstruction is realized by the Frenet–Serret (F–S) frame and sensing characteristics such as twisting, strain and temperature are systematically analyzed. Especially, the twisting characteristics of SMCF and MCF are compared and the feasibility of self-torsional compensation of SMCF is demonstrated. In addition, shape measurement experiments with three known shapes are performed. The mean relative error (MRE) for each shape is 0.49%, 1.90% and 5.13%, respectively. These results show that the proposed sensor can accurately measure 3D shapes with temperature and twisting compensation, enabling its application prospects in the online shape feedback of continuum surgical robots.

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References

  1. Y. Lu, B. Lu, B. Li, H. Guo, Y.H. Liu, IEEE Robot Autom Lett 6, 4835 (2021)

    Article  Google Scholar 

  2. X.T. Ha, M. Ourak, O. Al-Ahmad, D. Wu, G. Borghesan, A. Menciassi, and E. Vander Poorten, IEEE Sens J 21, 23422 (2021)

    Article  Google Scholar 

  3. R. Zhang, H. Liu, and J. Han, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 925 (2017).

  4. S. Sefati, R. Hegeman, F. Alambeigi, I. Iordachita, P. Kazanzides, H. Khanuja, R. H. Taylor, and M. Armand, IEEE/ASME Transactions on Mechatronics 26, 369–380 (2021).

  5. R. Xu, A. Yurkewich, R.V. Patel, IEEE Robot Autom Lett 1, 1052 (2016)

    Article  Google Scholar 

  6. F. Qi, B. Chen, S. She, S. Gao, Ind. Robot. 48, 259 (2020)

    Article  Google Scholar 

  7. J. Li, F. Zhang, H. Liu, J. Li, F. Zhang, H. Liu, J. Li, F. Zhang, H. Liu, J. Li, Z. Yang, Z. Jiang, IEEE Robot Autom Lett 7, 3130 (2022)

    Article  Google Scholar 

  8. Y. Chitalia, N.J. Deaton, S. Jeong, N. Rahman, J.P. Desai, IEEE Robot Autom Lett 5, 1712 (2020)

    Article  Google Scholar 

  9. V. Modes, T. Ortmaier, J. Burgner-Kahrs, IEEE Sens J 21, 6712 (2021)

    Article  ADS  Google Scholar 

  10. P. Jiao, Y. Xie, S. Wu, X. Liu, Materials 13, 2599 (2020)

    Article  ADS  Google Scholar 

  11. Z. Liu, S. Lu, D. Wang, Y. Guo, and L. Wu, Materials 15, (2022).

  12. V. Vekteris, M. Jurevicius, V. Turla, Appl Phys B 121, 203 (2015)

    Article  ADS  Google Scholar 

  13. I. Floris, J. Madrigal, S. Sales, P. A. Calderón, and J. M. Adam, Mech Syst Signal Process 140, (2020).

  14. A. Wolf, K. Bronnikov, S. Yakushin, A. Dostovalov, S. Zhuravlev, al Alexey Wolf, M. Salganskii, O. Egorova, S. Semjonov, and S. Babin, Seventh European Workshop on Optical Fibre Sensors (EWOFS 2019) 11199, 475 (2019).

  15. W. Bao, N. Sahoo, Z. Sun, C. Wang, S. Liu, Y. Wang, and L. Zhang, Opt Express 28, (2020).

  16. A. Halstuch and A. A. Ishaaya, Opt Lasers Eng 160, (2023).

  17. R. Idrisov, A. Lorenz, M. Rothhardt, and H. Bartelt, Sensors 22, (2022).

  18. R. Mahakud, J. Kumar, O. Prakash, S.K. Dixit, S.V. Nakhe, Appl Phys B 121, 283 (2015)

    Article  ADS  Google Scholar 

  19. J. Xin, W. Zhuang, X. Lou, L. Zhu, M. Dong, Opt. Eng. 58, 1 (2019)

    Article  Google Scholar 

  20. F. Khan, A. Denasi, D. Barrera, J. Madrigal, S. Sales, S. Misra, IEEE Sens J 19, 5878 (2019)

    Article  ADS  Google Scholar 

  21. T. Li, C. Shi, Y. Tan, and Z. Zhou, IEEE Sens J 17, (2017).

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Acknowledgements

This work was supported by the Key Project of Beijing Municipal Education Commission Science and Technology Program (No. KZ201911232044), the Beijing Nova Program of Science and Technology (No. Z191100001119052), the National Key Research and Development Program of China (No. 2020YFA0711200) and the National Natural Science Foundation of China (No. 52275517).

Funding

Funding was provided by the Key Project of Beijing Municipal Education Commission Science and Technology Program (No. KZ201911232044), the Beijing Nova Program of Science and Technology (No. Z191100001119052), the National Key Research and Development Program of China (No. 2020YFA0711200) and the National Natural Science Foundation of China (No. 52275517).

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Authors and Affiliations

  1. State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Nankai District, No. 92 Weijin Road, Tianjin, 300072, China

    Kangpeng Zhou

  2. Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, Haidian District, No. 12 Xiaoying East Road, QingheBeijing, 100192, China

    Lianqing Zhu, Guangkai Sun & Yanlin He

  3. Beijing Laboratory of Optical Fiber Sensing and System, Beijing Information Science and Technology University, Haidian District, No. 12 Xiaoying East Road, QingheBeijing, 100192, China

    Lianqing Zhu, Guangkai Sun & Yanlin He

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  1. Kangpeng Zhou
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  2. Lianqing Zhu
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  4. Yanlin He
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Contributions

Investigation, K.Z; Methodology, K.Z., G.S.; Writing - original draft, K.Z; Supervision, L.Z.; Writing – review & editing, G.S, Y.H, and L.Z.; Software, K.Z. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Lianqing Zhu.

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Zhou, K., Zhu, L., Sun, G. et al. FBG-based 3D shape sensor based on spun multi-core fibre for continuum surgical robots. Appl. Phys. B 129, 140 (2023). https://doi.org/10.1007/s00340-023-08082-z

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