[1] Continuum robot. https://https://www.cardion.cz/file/169/Hansen%
20Medical%20brochure-EU.pdf. Accessed: 2023-08-01.
[2] Minimally invasive surgery. https://medmovie.com/library_id/3255/topic/ahaw_
0182i/. Accessed: 2023-07-01.
[3] Soft endoscope. https://kclhammerlab.com/2018/research/
soft-self-propelled-endoscopic-robot/. Accessed: 2023-08-01.
[4] soft grasper. https://softroboticstoolkit.com/book/sdm-case-study. Accessed:
2023-08-01.
[5] H. Abidi, G. Gerboni, M. Brancadoro, J. Fras, A. Diodato, M. Cianchetti, H. Wurdemann,
K. Althoefer, and A. Menciassi. Highly dexterous 2-module soft robot for
intra-organ navigation in minimally invasive surgery. The International Journal of
Medical Robotics and Computer Assisted Surgery, 14(1):e1875, 2018.
[6] A. A. Abushagur, N. Arsad, M. Ibne Reaz, A. Ashrif, and A. Bakar. Advances in
bio-tactile sensors for minimally invasive surgery using the fibre bragg grating force
sensor technique: A survey. Sensors, 14(4):6633–6665, 2014.
[7] Y. Adagolodjo, F. Renda, and C. Duriez. Coupling numerical deformable models in global and reduced coordinates for the simulation of the direct and the inverse
kinematics of soft robots. IEEE Robotics and Automation Letters, 6(2):3910–3917,2021.
[8] C. C. Aggarwal et al. Neural networks and deep learning. Springer, 10(978):3, 2018.
[9] O. Al-Ahmad, M. Ourak, J. Vlekken, E. Lindner, and E. Vander Poorten. Threedimensional
catheter tip force sensing using multi-core fiber bragg gratings. Frontiers
in Robotics and AI, 10:1154494, 2023.
[10] M. Alam, R. Young, and R. Diaz-Nieto. Robotic liver surgery. In S. K¨u¸c¨uk, editor,
Latest Developments in Medical Robotics Systems, chapter 2. IntechOpen, Rijeka, 2021.
[11] T. Amadeo, D. Van Lewen, T. Janke, T. Ranzani, A. Devaiah, U. Upadhyay, and
S. Russo. Soft robotic deployable origami actuators for neurosurgical brain retraction.
Frontiers in Robotics and AI, 8:731010, 2022.
[12] J. D. Anderson. Fundamentals of Aerodynamics. New York, NY: McGraw Hill, sixth
edition, 2017.
[13] M. Antonilli, V. Sevas, M. L. Gasparri, A. A. Farooqi, and A. Papadia. Minimally invasive
surgery in gynecology. In Advances in Minimally Invasive Surgery. IntechOpen,
2021.
[14] C. Appiah, C. Arndt, K. Siemsen, A. Heitmann, A. Staubitz, and C. Selhuber-Unkel.
Living materials herald a new era in soft robotics. Advanced Materials, 31(36):1807747,
2019.
[15] J. Back, L. Lindenroth, R. Karim, K. Althoefer, K. Rhode, and H. Liu. New kinematic
multi-section model for catheter contact force estimation and steering. In 2016, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 2122–2127. IEEE, 2016.
[16] J. Back, L. Lindenroth, K. Rhode, and H. Liu. Three dimensional force estimation
for steerable catheters through bi-point tracking. Sensors and Actuators A: Physical,
279:404–415, 2018.
[17] J. Back, T. Manwell, R. Karim, K. Rhode, K. Althoefer, and H. Liu. Catheter contact
force estimation from shape detection using a real-time cosserat rod model. In 2015
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages
2037–2042. IEEE, 2015.
[18] Z. Bai, X. Cao, B. Xiong, Y. Dong, X. Sun, and W. Sun. Clinical effectiveness of distal
metatarsophalangeal mini-invasive osteotomy on hallux valgus. 2023.
[19] N. Bandari, J. Dargahi, and M. Packirisamy. Tactile sensors for minimally invasive
surgery: A review of the state-of-the-art, applications, and perspectives. Ieee Access,
8:7682–7708, 2019.
[20] J. Bao, W. Chen, and J. Xu. Kinematics modeling of a twisted and coiled polymerbased
elastomer soft robot. IEEE Access, 7:136792–136800, 2019.
[21] O. A. Bauchau and J. I. Craig. Euler-bernoulli beam theory. Structural analysis, pages
173–221, 2009.
[22] R. Berthold, M. N. Bartholdt, M. Wiese, S. Kahms, S. Spindeldreier, and A. Raatz.
A preliminary study of soft material robotic modelling: Finite element method and
cosserat rod model. In 2021 9th International Conference on Control, Mechatronics
and Automation (ICCMA), pages 7–13. IEEE, 2021.
[23] M. Bijjawara, U. Bidre, and S. Vijay. Minimally invasive spine surgery: Hurdles to be
crossed. Indian Journal of Neurosurgery, 3(01):008–013, 2014.
[24] D. Bonnet, T. Hirtzlin, A. Majumdar, T. Dalgaty, E. Esmanhotto, V. Meli, N. Castellani,
S. Martin, J.-F. Nodin, G. Bourgeois, et al. Bringing uncertainty quantification to
the extreme-edge with memristor-based Bayesian neural networks. Preprint, Research
Square, 2023.
[25] F. Bourier, C. Gianni, M. Dare, I. Deisenhofer, G. Hessling, T. Reents, S. Mohanty,
C. Trivedi, A. Natale, and A. AL-AHMAD. Fiberoptic contact-force sensing electrophysiological
catheters: how precise is the technology? Journal of cardiovascular
electrophysiology, 28(1):109–114, 2017.
[26] K. Chen, J. Zhang, N. M. Beeraka, M. Y. Sinelnikov, X. Zhang, Y. Cao, and P. Lu.
Robot-assisted minimally invasive breast surgery: Recent evidence with comparative
clinical outcomes. Journal of Clinical Medicine, 11(7):1827, 2022.
[27] P. Chen, Y. Yu, and Y. Liu. Variable curvature modelling method of continuum robots
with contraints. 2021.
[28] Y. Chen, L. Li, W. Li, Q. Guo, Z. Du, and Z. Xu. Chapter 2 - fundamentals of neural networks. In Y. Chen, L. Li, W. Li, Q. Guo, Z. Du, and Z. Xu, editors, AI Computing
Systems, pages 17–51. Morgan Kaufmann, 2024.
[29] D. Coban, S. Changoor, S. Saela, K. Sinha, K. Hwang, M. Faloon, and A. Emami. Obesity
does not adversely affect long-term outcomes of minimally invasive transforaminal
lumbar interbody fusion: a matched cohort analysis. Orthopedics, 45(4):203–208, 2022.
[30] M. V. Corniola, B. Debono, H. Joswig, J.-M. Lem´ee, and E. Tessitore. Enhanced recovery after spine surgery: review of the literature. Neurosurgical focus, 46(4):E2,
2019.
[31] E. M. P. Cosserat and F. Cosserat. Th´eorie des corps d´eformables. A. Hermann et fils,
1909.
[32] M. Dado and S. Al-Sadder. A new technique for large deflection analysis of nonprismatic
cantilever beams. Mechanics research communications, 32(6):692–703, 2005.
[33] A. B. Dawood, H. Godaba, and K. Althoefer. Silicone based capacitive e-skin sensor
for soft surgical robots. In Towards Autonomous Robotic Systems: 21st Annual Conference, TAROS 2020, Nottingham, UK, September 16, 2020, Proceedings 21, pages 62–65. Springer, 2020.
[34] C. Della Santina, A. Bicchi, and D. Rus. On an improved state parametrization for
soft robots with piecewise constant curvature and its use in model based control. IEEE
Robotics and Automation Letters, 5(2):1001–1008, 2020.
[35] S. O. Demir, U. Culha, A. C. Karacakol, A. Pena-Francesch, S. Trimpe, and M. Sitti.
Task space adaptation via the learning of gait controllers of magnetic soft millirobots.
The International journal of robotics research, 40(12-14):1331–1351, 2021.
[36] A. Di Maro, S. Creaco, M. Albini, M. Latiff, and M. Merlo. Radiographic results on
acetabular cup placement with the superpath technique: a retrospective study of 756
cases. BMC Musculoskeletal Disorders, 23(1):101, 2022.
[37] S. Dietsch, A. McDonald-Bowyer, E. Dimitrakakis, J. M. Coote, L. Lindenroth,
A. Stilli, and D. Stoyanov. Localization of interaction using fibre-optic shape sensing in
soft-robotic surgery tools. In 2022 IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS), pages 8057–8063. IEEE, 2022.
[38] C. Donkor, A. Gonzalez, M. R. Gallas, M. Helbig, C. Weinstein, and J. Rodriguez.
Current perspectives in robotic hernia repair. Robotic Surgery: Research and Reviews,
pages 57–67, 2017.
[39] W. Duan, T. Akinyemi, W. Du, J. Ma, X. Chen, F. Wang, O. Omisore, J. Luo,
H. Wang, and L. Wang. Technical and clinical progress on robot-assisted endovascular
interventions: A review. Micromachines, 14(1):197, 2023.
[40] K. M. El Dine, J. Sanchez, J. A. Corrales, Y. Mezouar, and J.-C. Fauroux. Forcetorque
sensor disturbance observer using deep learning. In Proceedings of the 2018
International Symposium on Experimental Robotics, pages 364–374. Springer, 2020.
[41] J.-H. Eum, J.-H. Park, K.-S. Song, S.-M. Lee, D.-W. Suh, and D.-J. Jo. Endoscopic
extreme transforaminal lumbar interbody fusion with large spacers: a technical note
and preliminary report. Orthopedics, 45(3):163–168, 2022.
[42] I. Floris, J. M. Adam, P. A. Calder´on, and S. Sales. Fiber optic shape sensors: A
comprehensive review. Optics and Lasers in Engineering, 139:106508, 2021.
[43] E. Franco, D. Rodr´ıguez Mu˜noz, R. Mat´ıa, A. Hern´andez-Madrid, I. S´anchez P´erez,
J. L. Zamorano, and J. Moreno. Contact force-sensing catheters: performance in
an ex vivo porcine heart model. Journal of Interventional Cardiac Electrophysiology, 53:141–150, 2018.
[44] K. C. Galloway, Y. Chen, E. Templeton, B. Rife, I. S. Godage, and E. J. Barth. Fiber optic shape sensing for soft robotics. Soft robotics, 6(5):671–684, 2019.
[45] J. Garcia, H. Sheitt, M. S. Bristow, C. Lydell, A. G. Howarth, B. Heydari, F. S. Prato, M. Drangova, R. E. Thornhill, P. Nery, et al. Left atrial vortex size and velocity distributions by 4d flow mri in patients with paroxysmal atrial fibrillation:
Associations with age and cha2ds2-vasc risk score. Journal of Magnetic Resonance Imaging, 51(3):871–884, 2020.
[46] P. C. Giulianotti, F. Sbrana, F. M. Bianco, E. F. Elli, G. Shah, P. Addeo, G. Caravaglios, and A. Coratti. Robot-assisted laparoscopic pancreatic surgery: singlesurgeon experience. Surgical endoscopy, 24:1646–1657, 2010.
[47] Z. Gong, J. Cheng, K. Hu, T. Wang, and L. Wen. An inverse kinematics method of a soft robotic arm with three-dimensional locomotion for underwater manipulation.
In 2018 IEEE International Conference on Soft Robotics (RoboSoft), pages 516–521. IEEE, 2018.
[48] S. Grazioso, G. Di Gironimo, and B. Siciliano. A geometrically exact model for soft continuum robots: The finite element deformation space formulation. Soft robotics, 6(6):790–811, 2019.
[49] C. Guo, X. Li, C. Li, Y. Xu, M. Cai, and X. Xu. A new minimally invasive surgery of
hallux valgus: Technique and preliminary outcomes. 2020.
[50] H. Guo, F. Ju, Y. Cao, F. Qi, D. Bai, Y. Wang, and B. Chen. Continuum robot shape
estimation using permanent magnets and magnetic sensors. Sensors and Actuators A:
Physical, 285:519–530, 2019.
[51] R. Hao, E. Erdem Tuna, and M. C. C¸ avu¸so˘glu. Contact stability and contact safety
of a magnetic resonance imaging-guided robotic catheter under heart surface motion. Journal of Dynamic Systems, Measurement, and Control, 143(7), 2021.
[52] R. Hao, T. Greigarn, and M. C. C¸ avu¸so˘glu. Contact stability analysis of magneticallyactuated
robotic catheter under surface motion. In 2020 IEEE International Conference
on Robotics and Automation (ICRA), pages 4455–4462. IEEE, 2020.
[53] R. Hao, N. L. Poirot, and M. C. C¸ avu¸so˘glu. Analysis of contact stability and contact safety of a robotic intravascular cardiac catheter under blood flow disturbances. In
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 3216–3223. IEEE, 2020.
[54] Y. He, L. Gao, Y. Bai, H. Zhu, G. Sun, L. Zhu, and H. Xu. Stretchable optical fibre sensor for soft surgical robot shape reconstruction. Optica Applicata, 51(4), 2021.
[55] A. Hooshiar, N. M. Bandari, and J. Dargahi. Image-based estimation of contact forces
on catheters for robot-assisted cardiovascular intervention. In Hamlyn Symposium on Medical Robotics, pages 119–120, 2018.
[56] A. Hooshiar, S. Najarian, and J. Dargahi. Haptic telerobotic cardiovascular intervention: a review of approaches, methods, and future perspectives. IEEE reviews in biomedical engineering, 13:32–50, 2019.
[57] A. Hooshiar, A. Sayadi, M. Jolaei, and J. Dargahi. Accurate estimation of tip force on tendon-driven catheters using inverse cosserat rod model. In 2020 International Conference on Biomedical Innovations and Applications (BIA), pages 37–40. IEEE, 2020.
[58] A. Hooshiar, A. Sayadi, M. Jolaei, and J. Dargahi. Analytical tip force estimation on tendon-driven catheters through inverse solution of cosserat rod model. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 1829–1834. IEEE, 2021.
[59] B. N. G. I. Isbister, A. An integrated kinematic modeling and experimental approach for an active endoscope. Front. Robot. AI, 8, 2021.
[60] M. Ji, Q. Li, I. H. Cho, and J. Kim. Rapid design and analysis of microtube pneumatic actuators using line-segment and multi-segment euler–bernoulli beam models. Micromachines, 10(11):780, 2019.
[61] A. S. John, I. Caturegli, N. S. Kubicki, and S. M. Kavic. The rise of minimally invasive surgery: 16 year analysis of the progressive replacement of open surgery with laparoscopy. JSLS: Journal of the Society of Laparoscopic & Robotic Surgeons, 24(4),
2020.
[62] M. Jolaei, A. Hooshiar, and J. Dargahi. Displacement-based model for estimation of
contact force between rfa catheter and atrial tissue with ex-vivo validation. In 2019
IEEE International Symposium on Robotic and Sensors Environments (ROSE), pages
1–7. IEEE, 2019.
[63] M. T. Kanada, A. Switching between continuum and discrete states in a continuum robot with dislocatable joints. IEEE Access, 9:34859–34867, 2021.
[64] R. Khoshbakht, M. Kheiri, J. Dargahi, and A. Hooshiar. Effects of blood flow on the tip contact force of cardiac ablation catheters. In 2022 IEEE International Symposium on Robotic and Sensors Environments (ROSE), pages 1–7. IEEE, 2022.
[65] Y. Kim, G. A. Parada, S. Liu, and X. Zhao. Ferromagnetic soft continuum robots. Science Robotics, 4(33):eaax7329, 2019.
[66] B. P. Krijthe, A. Kunst, E. J. Benjamin, G. Y. Lip, O. H. Franco, A. Hofman, J. C. Witteman, B. H. Stricker, and J. Heeringa. Projections on the number of individuals with atrial fibrillation in the european union, from 2000 to 2060. European heart
journal, 34(35):2746–2751, 2013.
[67] T. K¨uffer, A. Haeberlin, S. Knecht, S. H. Baldinger, A. Madaffari, J. Seiler, A. M¨uhl, H. Tanner, L. Roten, and T. Reichlin. Validation of the accuracy of contact force measurement by contemporary force-sensing ablation catheters. Journal of cardiovascular
electrophysiology, 34(2):292–299, 2023.
[68] T. Kurmann, P. Marquez Neila, X. Du, P. Fua, D. Stoyanov, S. Wolf, and R. Sznitman.
Simultaneous recognition and pose estimation of instruments in minimally invasive
surgery. In Medical Image Computing and Computer-Assisted Intervention- MICCAI
2017: 20th International Conference, Quebec City, QC, Canada, September 11-13,
2017, Proceedings, Part II 20, pages 505–513. Springer, 2017.
[69] N. Lang, M. J. Pereira, Y. Lee, I. Friehs, N. V. Vasilyev, E. N. Feins, K. Ablasser, E. D. O’Cearbhaill, C. Xu, A. Fabozzo, et al. A blood-resistant surgical glue for
minimally invasive repair of vessels and heart defects. Science translational medicine, 6(218):218ra6–218ra6, 2014.
[70] J. Lantz, V. Gupta, L. Henriksson, M. Karlsson, A. Persson, C.-J. Carlh¨all, and T. Ebbers. Impact of pulmonary venous inflow on cardiac flow simulations: comparison with in vivo 4d flow mri. Annals of biomedical engineering, 47:413–424, 2019.
[71] K. Lee. Large deflections of cantilever beams of non-linear elastic material under a
combined loading. International Journal of Non-Linear Mechanics, 37(3):439–443, 2002.
[72] M. Lerotic and G.-Z. Yang. The use of super resolution in robotic assisted minimally invasive surgery. In Medical Image Computing and Computer-Assisted Intervention– MICCAI 2006: 9th International Conference, Copenhagen, Denmark, October 1-6, 2006. Proceedings, Part I 9, pages 462–469. Springer, 2006.
[73] K. Li, F. Liu, P. Liu, C. Wei, X. Li, et al. Clinical effect and aesthetic evaluation of minimally invasive implant therapy. Emergency Medicine International, 2023, 2023.
[74] L. Li, T. Jin, Y. Tian, F. Yang, and F. Xi. Design and analysis of a square-shaped continuum robot with better grasping ability. IEEE Access, 7:57151–57162, 2019.
[75] G. Lippi, F. Sanchis-Gomar, and G. Cervellin. Global epidemiology of atrial fibrillation: an increasing epidemic and public health challenge. International Journal of Stroke, 16(2):217–221, 2021.
[76] P. Lloyd, Z. Koszowska, M. Di Lecce, O. Onaizah, J. H. Chandler, and P. Valdastri. Feasibility of fiber reinforcement within magnetically actuated soft continuum robots. Frontiers in Robotics and AI, 8:715662, 2021.
[77] Y. Lou, T. Yang, D. Luo, J. Wu, and Y. Dong. A novel catheter distal contact force sensing for cardiac ablation based on fiber bragg grating with temperature compensation. Sensors, 23(5):2866, 2023.
[78] G. Mariani, L. Bruselli, T. Kuwert, E. E. Kim, A. Flotats, O. Israel, M. Dondi, and N. Watanabe. A review on the clinical uses of spect/ct. European journal of nuclear medicine and molecular imaging, 37:1959–1985, 2010.
[79] A. Mate. The frenet-serret formulas. Brooklyn Collage Of The City University Of New York, izdano, 19, 2017.
[80] H. Nakagawa and W. M. Jackman. The role of contact force in atrial fibrillation
ablation. Journal of atrial fibrillation, 7(1), 2014.
[81] N. Naughton, J. Sun, A. Tekinalp, T. Parthasarathy, G. Chowdhary, and M. Gazzola.
Elastica: A compliant mechanics environment for soft robotic control. IEEE Robotics
and Automation Letters, 6(2):3389–3396, 2021.
[82] R. M. Neal. Bayesian learning for neural networks, volume 118. Springer Science &
Business Media, 2012.
[83] J. Negrillo-C´ardenas, J.-R. Jim´enez-P´erez, J. Madeira, and F. R. Feito. A virtual
reality simulator for training the surgical reduction of patient-specific supracondylar
humerus fractures. International Journal of Computer Assisted Radiology and Surgery,
17(1):65–73, 2022.
[84] G. Olson, R. L. Hatton, J. A. Adams, and Y. Meng¨u¸c. An euler–bernoulli beam model
for soft robot arms bent through self-stress and external loads. International Journal
of Solids and Structures, 207:113–131, 2020.
[85] A. Omran, A. A. Arifi, and A. Mohamed. Echocardiography in mitral stenosis. Journal
of the Saudi heart Association, 23(1):51–58, 2011.
[86] D. Padmanabhan, P. S. M. Rao, H. J. Pandya, et al. Force sensing technologies for
catheter ablation procedures. Mechatronics, 64:102295, 2019.
[87] L. Pancaldi, L. Noseda, A. Dolev, A. Fanelli, D. Ghezzi, A. J. Petruska, and M. S.
Sakar. Locomotion of sensor-integrated soft robotic devices inside sub-millimeter arteries
with impaired flow conditions. Advanced Intelligent Systems, 4(5):2100247, 2022.
[88] A. Parisi, D. Reim, F. Borghi, N. T. Nguyen, F. Qi, A. Coratti, F. Cianchi, M. Cesari,
F. Bazzocchi, O. Alimoglu, et al. Minimally invasive surgery for gastric cancer: A
comparison between robotic, laparoscopic and open surgery. World journal of gastroenterology,
23(13):2376, 2017.
[89] T. Pfaff, M. Fortunato, A. Sanchez-Gonzalez, and P. W. Battaglia. Learning meshbased
simulation with graph networks. arXiv preprint arXiv:2010.03409, 2020.
[90] P. Polygerinos, T. Schaeffter, L. Seneviratne, and K. Althoefer. A fibre-optic cathetertip
force sensor with mri compatibility: A feasibility study. In 2009 Annual International
Conference of the IEEE Engineering in Medicine and Biology Society, pages
1501–1054. IEEE, 2009.
[91] F. Qi, F. Ju, D. Bai, Y. Wang, and B. Chen. Kinematic analysis and navigation
method of a cable-driven continuum robot used for minimally invasive surgery. The
International Journal of Medical Robotics and Computer Assisted Surgery, 15(4):e2007,
2019.
[92] K. Rajappan and M. Ginks. Catheter ablation of persistent atrial fibrillation. Future
Cardiology, 10(4):553–562, 2014.
[93] T. Reichlin, S. H. Baldinger, E. Pruvot, L. Bisch, P. Ammann, D. Altmann, B. Berte,
R. Kobza, L. Haegeli, C. Schlatzer, et al. Impact of contact force sensing technology
on outcome of catheter ablation of idiopathic pre-mature ventricular contractions
originating from the outflow tracts. EP Europace, 23(4):603–609, 2021.
[94] Z. Ren, R. Zhang, R. H. Soon, Z. Liu, W. Hu, P. R. Onck, and M. Sitti. Soft-bodied
adaptive multimodal locomotion strategies in fluid-filled confined spaces. Science advances,
7(27):eabh2022, 2021.
[95] R. Richa, A. P. B´o, and P. Poignet. Robust 3d visual tracking for robotic-assisted cardiac
interventions. In Medical Image Computing and Computer-Assisted Intervention–
MICCAI 2010: 13th International Conference, Beijing, China, September 20-24, 2010,
Proceedings, Part I 13, pages 267–274. Springer, 2010.
[96] R. J. Roesthuis and S. Misra. Steering of multisegment continuum manipulators using
rigid-link modeling and fbg-based shape sensing. IEEE transactions on robotics,
32(2):372–382, 2016.
[97] G. Runge, M. Wiese, L. G¨unther, and A. Raatz. A framework for the kinematic modeling
of soft material robots combining finite element analysis and piecewise constant
curvature kinematics. In 2017 3rd International Conference on Control, Automation
and Robotics (ICCAR), pages 7–14. IEEE, 2017.
[98] S. K. Sahu, C. Sozer, B. Rosa, I. Tamadon, P. Renaud, and A. Menciassi. Shape reconstruction
processes for interventional application devices: State of the art, progress,
and future directions. Frontiers in Robotics and AI, 8:758411, 2021.
[99] R. Sanchez-Matilla, M. Robu, I. Luengo, and D. Stoyanov. Scalable joint detection
and segmentation of surgical instruments with weak supervision. In International
Conference on Medical Image Computing and Computer-Assisted Intervention, pages
501–511. Springer, 2021.
[100] A. Sayadi, H. R. Nourani, M. Jolaei, J. Dargahi, and A. Hooshiar. Force estimation on
steerable catheters through learning-from-simulation with ex-vivo validation. In 2021
International Symposium on Medical Robotics (ISMR), pages 1–6. IEEE, 2021.
[101] A. Sayadi, H. R. Nourani, M. Jolaei, J. Dargahi, and A. Hooshiar. Force estimation on steerable catheters through learning-from-simulation with ex-vivo validation. In 2021
International Symposium on Medical Robotics (ISMR), pages 1–6. IEEE, 2021.
[102] C. Semler, G. X. Li, and M. Paıdoussis. The non-linear equations of motion of pipes
conveying fluid. Journal of Sound and Vibration, 169(5):577–599, 1994.
[103] I. S. Shchelik, J. V. Molino, and K. Gademann. Biohybrid microswimmers against
bacterial infections. Acta Biomaterialia, 136:99–110, 2021.
[104] J. Shi, J. C. Frantz, A. Shariati, A. Shiva, J. S. Dai, D. Martins, and H. A. Wurdemann.
Screw theory-based stiffness analysis for a fluidic-driven soft robotic manipulator. In 2021 IEEE International Conference on Robotics and Automation (ICRA), pages 11938–11944. IEEE, 2021.
[105] H. R. Shin, K. Lee, H. W. Yu, S.-j. Kim, Y. J. Chai, J. Y. Choi, and K. E. Lee. Comparison of perioperative outcomes using the da vinci s, si, x, and xi robotic platforms for baba robotic thyroidectomy. Medicina, 57(10):1130, 2021.
[106] J. So, U. Kim, Y. B. Kim, D.-Y. Seok, S. Y. Yang, K. Kim, J. H. Park, S. T. Hwang, Y. J. Gong, and H. R. Choi. Shape estimation of soft manipulator using stretchable sensor. Cyborg and Bionic Systems, 2021.
[107] C. Song. History and current situation of shape memory alloys devices for minimally invasive surgery. TOMDJ, 2:24–31, 2010.
[108] S. Song, C. Zhang, L. Liu, and M. Q.-H. Meng. Preliminary study on magnetic tracking-based planar shape sensing and navigation for flexible surgical robots in transoral surgery: methods and phantom experiments. International journal of computer assisted radiology and surgery, 13:241–251, 2018.
[109] M. Sun, C. Tian, L. Mao, X. Meng, X. Shen, B. Hao, X. Wang, H. Xie, and L. Zhang. Reconfigurable magnetic slime robot: deformation, adaptability, and multifunction. Advanced Functional Materials, 32(26):2112508, 2022.
[110] S. S. Tabatabaei, M. Kheiri, and J. Dargahi. Dynamics and stability of imperfect flexible cylinders in axial flow. Journal of Fluids and Structures, 105:103321, 2021.
[111] K. Takashima, R. Shimomura, T. Kitou, H. Terada, K. Yoshinaka, and K. Ikeuchi. Contact and friction between catheter and blood vessel. Tribology International, 40(2):319– 328, 2007.
[112] J. Thiboutot, A. C. Argento, J. Akulian, H. J. Lee, A. DeMaio, C. M. Kapp, M. M. Wahidi, and L. Yarmus. Accuracy of pulmonary nodule sampling using robotic assisted bronchoscopy with shape sensing, fluoroscopy, and radial endobronchial ultrasound (the accuracy study). Respiration, 101(5):485–493, 2022.
[113] T. G. Thuruthel, E. Falotico, M. Cianchetti, F. Renda, and C. Laschi. Learning global inverse statics solution for a redundant soft robot. In Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics, volume 2,
pages 303–310, 2016.
[114] T. G. Thuruthel, E. Falotico, F. Renda, and C. Laschi. Model-based reinforcement learning for closed-loop dynamic control of soft robotic manipulators. IEEE Transactions on Robotics, 35(1):124–134, 2018.
[115] J. Tian, K. O. Afebu, Z. Wang, Y. Liu, and S. Prasad. Dynamic analysis of a soft capsule robot self-propelling in the small intestine via finite element method. Nonlinear Dynamics, 111(11):9777–9798, 2023.
[116] J. Till, V. Aloi, and C. Rucker. Real-time dynamics of soft and continuum robots based on cosserat rod models. The International Journal of Robotics Research, 38(6):723–746, 2019.
[117] T. Torkaman, M. Roshanfar, J. Dargahi, and A. Hooshiar. Analytical modeling and experimental validation of a gelatin-based shape sensor for soft robots. In 2022 International Symposium on Medical Robotics (ISMR), pages 1–7. IEEE, 2022.
[118] V. K. Venkiteswaran, J. Sikorski, and S. Misra. Shape and contact force estimation of continuum manipulators using pseudo rigid body models. Mechanism and machine theory, 139:34–45, 2019.
[119] E. Vignali, E. Gasparotti, K. Capellini, B. M. Fanni, L. Landini, V. Positano, and S. Celi. Modeling biomechanical interaction between soft tissue and soft robotic instruments: importance of constitutive anisotropic hyperelastic formulations. The International Journal of Robotics Research, 40(1):224–235, 2021.
[120] C. Wang, Y. Wu, X. Dong, M. Armacki, and M. Sitti. In situ sensing physiological properties of biological tissues using wireless miniature soft robots. Science advances, 9(23):eadg3988, 2023.
[121] H. Wang, M. Totaro, and L. Beccai. Toward perceptive soft robots: Progress and challenges. Advanced Science, 5(9):1800541, 2018.
[122] P. Wang, S. Zhang, Z. Liu, Y. Huang, J. Huang, X. Huang, J. Chen, B. Fang, and D. Peng. Smart laparoscopic grasper integrated with fiber bragg grating based tactile sensor for real-time force feedback. Journal of Biophotonics, 15(5):e202100331, 2022.
[123] X.-Q. Wang, Y. Design and fabrication of a new dual-arm soft robotic manipulator. Actuators, 8:5, 2019.\
[124] I. Waters, D. Jones, A. Alazmani, and P. Culmer. Encouraging and detecting preferential
incipient slip for use in slip prevention in robot-assisted surgery. Sensors,
22(20):7956, 2022.
[125] A. Wutzler, T. Wolber, W. Haverkamp, and L.-H. Boldt. Robotic ablation of atrial
fibrillation. JoVE (Journal of Visualized Experiments), (99):e52560, 2015.
[126] N. Xia, G. Zhu, X.Wang, Y. Dong, and L. Zhang. Multicomponent and multifunctional
integrated miniature soft robots. Soft Matter, 18(39):7464–7485, 2022.
[127] R. Xu, A. Yurkewich, and R. V. Patel. Curvature, torsion, and force sensing in continuum robots using helically wrapped fbg sensors. IEEE Robotics and Automation Letters, 1(2):1052–1059, 2016.
[128] W. Xu, M. Auli, and S. Clark. Ccg supertagging with a recurrent neural network.
In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics
and the 7th International Joint Conference on Natural Language Processing
(Volume 2: Short Papers), pages 250–255, 2015.
[129] H. Z. Yang, E. S. Clinical comparison of 3 different double eyelid surgeries. Ann Plast
Surg, 88:138–143, 2021.
[130] H. Yuan, P. W. Y. Chiu, and Z. Li. Shape-reconstruction-based force sensing method
for continuum surgical robots with large deformation. IEEE Robotics and Automation
Letters, 2(4):1972–1979, 2017.
[131] X. Zhang, M. Du, J. Zhang, and H. Li. Application of digital minimally invasive
medicine and visual simulation in surgery. In 7th International Conference on Management,
Education, Information and Control (MEICI 2017), pages 873–876. Atlantis Press, 2017.
[132] X. Zhang, J. Kow, D. Jones, G. de Boer, A. Ghanbari, A. Serjouei, P. Culmer, and A. Alazmani. Adjustable compliance soft sensor via an elastically inflatable fluidic dome. Sensors, 21(6):1970, 2021.
[133] H. Zhao, J. Jalving, R. Huang, R. Knepper, A. Ruina, and R. Shepherd. A helping hand: Soft orthosis with integrated optical strain sensors and emg control. IEEE Robotics & Automation Magazine, 23(3):55–64, 2016.