Medical Technologies and Challenges of Robot-Assisted Minimally Invasive Intervention and Diagnostics

Literature Cited

1. 1.  Scott W Jr 1969. The development of the cystoscope. From “lichtleiter” to fiber optics. Investig. Urol. 6:657–61
   [Google Scholar]
2. 2.  Samplaski MK, Jones JS 2009. Two centuries of cystoscopy: the development of imaging, instrumentation and synergistic technologies. BJU Int 103:154–58
   [Google Scholar]
3. 3.  Litynski GS 1997. Laparoscopy—the early attempts: spotlighting Georg Kelling and Hans Christian Jacobaeus. JSLS 1:83–85
   [Google Scholar]
4. 4.  Semm K 1983. Endoscopic appendectomy. Endoscopy 15:59–64
   [Google Scholar]
5. 5.  Gagner M, Pomp A 1994. Laparoscopic pylorus-preserving pancreatoduodenectomy. Surg. Endosc. 8:408–10
   [Google Scholar]
6. 6.  Simaan N, Taylor RH, Choset H 2015. Intelligent surgical robots with situational awareness: from good to great surgeons. Mech. Eng. 137:S3
   [Google Scholar]
7. 7.  Hounsfield GN 1973. Computerized transverse axial scanning (tomography): part 1. Description of system. Br. J. Radiol. 46:1016–22
   [Google Scholar]
8. 8.  Yohannes P, Rotariu P, Pinto P, Smith AD, Lee BR 2002. Comparison of robotic versus laparoscopic skills: Is there a difference in the learning curve?. Urology 60:39–45
   [Google Scholar]
9. 9.  Hanzly M, Frederick A, Creighton T, Atwood K, Mehedint D et al. 2015. Learning curves for robot-assisted and laparoscopic partial nephrectomy. J. Endourol. 29:297–303
   [Google Scholar]
10. 10. Intuitive Surg. 2013. Annual report 2013 Rep., Intuitive Surg., Sunnyvale, CA. http://phx.corporate-ir.net/External.File?item=UGFyZW50SUQ9MjIzOTk3fENoaWxkSUQ9LTF8VHlwZT0z&t=1
    [Google Scholar]
11. 11. Intuitive Surg. 2016. Annual report 2016 Rep., Intuitive Surg., Sunnyvale, CA. http://www.annualreports.com/HostedData/AnnualReports/PDF/NASDAQ_ISRG_2016.pdf
    [Google Scholar]
12. 12.  Baek SJ, Kim SH 2014. Robotics in general surgery: an evidence-based review. Asian J. Endosc. Surg. 7:117–23
    [Google Scholar]
13. 13.  Grimsby GM, Dwyer ME, Jacobs MA, Ost MC, Schneck FX et al. 2015. Multi-institutional review of outcomes of robot-assisted laparoscopic extravesical ureteral reimplantation. J. Urol. 193:1791–95
    [Google Scholar]
14. 14.  Rattner D, Kalloo A 2006. ASGE/SAGES working group on natural orifice translumenal endoscopic surgery. Surg. Endosc. 20:329–33
    [Google Scholar]
15. 15.  Romanelli JR, Earle DB 2009. Single-port laparoscopic surgery: an overview. Surg. Endosc. 23:1419–27
    [Google Scholar]
16. 16.  Tiwari MM, Reynoso JF, Lehman AC, Tsang AW, Farritor SM, Oleynikov D 2010. In vivo miniature robots for natural orifice surgery: state of the art and future perspectives. World J. Gastrointest. Surg. 2:217–23
    [Google Scholar]
17. 17.  Samarasekera D, Kaouk JH 2014. Robotic single port surgery: current status and future considerations. Indian J. Urol. 30:326
    [Google Scholar]
18. 18.  Morelli L, Guadagni S, Di Franco G, Palmeri M, Di Candio G, Mosca F 2016. Da Vinci single site^© surgical platform in clinical practice: a systematic review. Int. J. Med. Robot. Comput. Assist. Surg. 12:724–34
    [Google Scholar]
19. 19.  Bae SU, Jeong WK, Baek SK 2017. Current status of robotic single-port colonic surgery. Int. J. Med. Robot. Comput. Assist. Surg. 13:e1735
    [Google Scholar]
20. 20.  Haber GP, White MA, Autorino R, Escobar PF, Kroh MD et al. 2010. Novel robotic da Vinci instruments for laparoendoscopic single-site surgery. Urology 76:1279–82
    [Google Scholar]
21. 21.  Vitiello V, Lee SL, Cundy T, Yang GZ 2013. Emerging robotic platforms for minimally invasive surgery. IEEE Rev. Biomed. Eng. 6:111–26
    [Google Scholar]
22. 22.  Marcus HJ, Seneci CA, Payne CJ, Nandi D, Darzi A, Yang GZ 2014. Robotics in keyhole transcranial endoscope-assisted microsurgery: a critical review of existing systems and proposed specifications for new robotic platforms. Neurosurgery 10:84–95
    [Google Scholar]
23. 23.  Zhao J, Feng B, Zheng MH, Xu K 2015. Surgical robots for SPL and NOTES: a review. Minim. Invasive Ther. Allied Technol. 24:8–17
    [Google Scholar]
24. 24.  Arkenbout EA, Henselmans PW, Jelínek F, Breedveld P 2015. A state of the art review and categorization of multi-branched instruments for NOTES and SILS. Surg. Endosc. 29:1281–96
    [Google Scholar]
25. 25.  Orekhov A, Abah C, Simaan N 2018. Snake-like robots for minimally invasive, single port, and intraluminal surgeries. The Encyclopedia of Medical Robotics, Vol. 1, Minimally Invasive Surgical Robotics JP Desai, R Patel, A Ferreira, S Agrawal Hackensack, NJ: World Sci. In press
    [Google Scholar]
26. 26.  Lehman AC, Dumpert J, Wood NA, Redden L, Visty AQ et al. 2009. Natural orifice cholecystectomy using a miniature robot. Surg. Endosc. 23:260–66
    [Google Scholar]
27. 27.  Piccigallo M, Scarfogliero U, Quaglia C, Petroni G, Valdastri P et al. 2010. Design of a novel bimanual robotic system for single-port laparoscopy. IEEE/ASME Trans. Mechatron. 15:871–78
    [Google Scholar]
28. 28.  Lee H, Choi Y, Yi BJ 2012. Stackable 4-bar manipulators for single port access surgery. IEEE/ASME Trans. Mechatron. 17:157–66
    [Google Scholar]
29. 29.  Cheon B, Gezgin E, Ji DK, Tomikawa M, Hashizume M et al. 2014. A single port laparoscopic surgery robot with high force transmission and a large workspace. Surg. Endosc. 28:2719–29
    [Google Scholar]
30. 30.  Choi H, Kwak HS, Lim YA, Kim HJ 2014. Surgical robot for single-incision laparoscopic surgery. IEEE Trans. Biomed. Eng. 61:2458–66
    [Google Scholar]
31. 31.  Hendrick RJ, Mitchell CR, Herrell SD, Webster RJ 2015. Hand-held transendoscopic robotic manipulators: a transurethral laser prostate surgery case study. Int. J. Robot. Res. 34:1559–72
    [Google Scholar]
32. 32.  Simaan N, Bajo A, Reiter A, Wang L, Allen P, Fowler D 2013. Lessons learned using the insertable robotic effector platform (IREP) for single port access surgery. J. Robot. Surg. 7:235–40
    [Google Scholar]
33. 33.  Hendrick RJ, Herrell SD, Webster RJ 2014. A multi-arm hand-held robotic system for transurethral laser prostate surgery. 2014 IEEE International Conference on Robotics and Automation (ICRA)2850–55 New York: IEEE
    [Google Scholar]
34. 34.  Degani A, Choset H, Wolf A, Zenati MA 2006. Highly articulated robotic probe for minimally invasive surgery. 2006 IEEE International Conference on Robotics and Automation4167–72 New York: IEEE
    [Google Scholar]
35. 35.  Simaan N, Kai Xu K, Wei W, Kapoor A, Kazanzides P et al. 2009. Design and integration of a telerobotic system for minimally invasive surgery of the throat. Int. J. Robot. Res. 28:1134–53
    [Google Scholar]
36. 36.  Ding J, Xu K, Goldman R, Allen P, Fowler D, Simaan N 2010. Design, simulation and evaluation of kinematic alternatives for insertable robotic effectors platforms in single port access surgery. 2010 IEEE International Conference on Robotics and Automation 1053–58 New York: IEEE
    [Google Scholar]
37. 37.  Lee J, Kim J, Lee KK, Hyung S, Kim YJ et al. 2014. Modeling and control of robotic surgical platform for single-port access surgery. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems3489–95 New York: IEEE
    [Google Scholar]
38. 38.  Jayender J, Azizian M, Patel RV 2008. Autonomous image-guided robot-assisted active catheter insertion. IEEE Trans. Robot. 24:858–71
    [Google Scholar]
39. 39.  Jayender J, Patel RV, Nikumb S 2009. Robot-assisted active catheter insertion: algorithms and experiments. Int. J. Robot. Res. 28:1101–17
    [Google Scholar]
40. 40.  Penning RS, Jung J, Borgstadt JA, Ferrier NJ, Zinn MR 2011. Towards closed loop control of a continuum robotic manipulator for medical applications. 2011 IEEE International Conference on Robotics and Automation (ICRA)4822–27 New York: IEEE
    [Google Scholar]
41. 41.  Penning RS, Jung J, Ferrier NJ, Zinn MR 2012. An evaluation of closed-loop control options for continuum manipulators. 2012 IEEE International Conference on Robotics and Automation5392–97 New York: IEEE
    [Google Scholar]
42. 42.  Bajo A, Goldman RE, Simaan N 2011. Configuration and joint feedback for enhanced performance of multi-segment continuum robots. 2011 IEEE International Conference on Robotics and Automation2905–12 New York: IEEE
    [Google Scholar]
43. 43.  Webster RJ, Romano JM, Cowan NJ 2008. Kinematics and calibration of active cannulas. 2008 IEEE International Conference on Robotics and Automation3888–95 New York: IEEE
    [Google Scholar]
44. 44.  Camarillo DB, Carlson CR, Salisbury JK 2009. Configuration tracking for continuum manipulators with coupled tendon drive. IEEE Trans. Robot. 25:798–808
    [Google Scholar]
45. 45.  Murphy RJ, Kutzer MD, Segreti SM, Lucas BC, Armand M 2014. Design and kinematic characterization of a surgical manipulator with a focus on treating osteolysis. Robotica 32:835–50
    [Google Scholar]
46. 46.  Wang L, Simaan N 2014. Investigation of error propagation in multi-backbone continuum robots. Advances in Robot Kinematics J Lenarćić, O Khatib 385–94 Cham, Switz: Springer
    [Google Scholar]
47. 47.  Jang C, Ha J, Dupont PE, Park FC 2016. Toward on-line parameter estimation of concentric tube robots using a mechanics-based kinematic model. 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems2400–5 New York: IEEE
    [Google Scholar]
48. 48.  Guthart G, Salisbury JKJ 2000. The Intuitive^TM telesurgery system: overview and application. Millennium Conference: IEEE International Conference on Robotics and Automation 1618–21 New York: IEEE
    [Google Scholar]
49. 49.  Robinson G, Davies J 1999. Continuum robots – a state of the art. 1999 IEEE International Conference on Robotics and Automation 42849–54 New York: IEEE
    [Google Scholar]
50. 50.  Webster R, Jones B 2010. Design and kinematic modeling of constant curvature continuum robots: a review. Int. J. Robot. Res. 29:1661–83
    [Google Scholar]
51. 51.  Chirikjian G 2015. Conformational modeling of continuum structures in robotics and structural biology: a review. Adv. Robot. 29:817–29
    [Google Scholar]
52. 52.  Chiang LS, Jay PS, Valdastri P, Menciassi A, Dario P 2009. Tendon sheath analysis for estimation of distal end force and elongation. 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics332–37 New York: IEEE
    [Google Scholar]
53. 53.  Roy R, Wang L, Simaan N 2017. Modeling and estimation of friction, extension, and coupling effects in multisegment continuum robots. IEEE/ASME Trans. Mechatron. 22:909–20
    [Google Scholar]
54. 54.  Agrawal V, Peine WJ, Yao B, Choi S 2010. Control of cable actuated devices using smooth backlash inverse. 2010 IEEE International Conference on Robotics and Automation1074–79 New York: IEEE
    [Google Scholar]
55. 55.  Xu K, Simaan N 2010. Intrinsic wrench estimation and its performance index for multisegment continuum robots. IEEE Trans. Robot. 26:555–61
    [Google Scholar]
56. 56.  Kaneko M, Paetsch W, Tolle H 1992. Input-dependent stability of joint control of tendon-driven robot hands. IEEE Trans. Ind. Electron. 39:96–104
    [Google Scholar]
57. 57.  Palli G, Borghesan G, Melchiorri C 2012. Modeling, identification, and control of tendon-based actuation systems. IEEE Trans. Robot. 28:277–90
    [Google Scholar]
58. 58.  Phee S, Low S, Dario P, Menciassi A 2010. Tendon sheath analysis for estimation of distal end force and elongation for sensorless distal end. Robotica 28:1073–82
    [Google Scholar]
59. 59.  Agrawal V, Peine W, Yao B 2010. Modeling of transmission characteristics across a cable-conduit system. IEEE Trans. Robot. 26:914–24
    [Google Scholar]
60. 60.  Kato T, Okumura I, Song SE, Golby AJ, Hata N 2015. Tendon-driven continuum robot for endoscopic surgery: preclinical development and validation of a tension propagation model. IEEE/ASME Trans. Mechatron. 20:2252–63
    [Google Scholar]
61. 61.  Xu K, Simaan N 2006. Actuation compensation for flexible surgical snake-like robots with redundant remote actuation. 2006 IEEE International Conference on Robotics and Automation4148–54 New York: IEEE
    [Google Scholar]
62. 62.  Kesner SB, Howe RD 2011. Position control of motion compensation cardiac catheters. IEEE Trans. Robot. 27:1045–55
    [Google Scholar]
63. 63.  Kitagawa M, Okamura AM, Bethea BT, Gott VL, Baumgartner WA 2002. Analysis of suture manipulation forces for teleoperation with force feedback. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2002 T Dohi, R Kikinis 155–62 Berlin: Springer
    [Google Scholar]
64. 64.  Fischer GS, Akinbiyi T, Saha S, Zand J, Talamini M et al. 2006. Ischemia and force sensing surgical instruments for augmenting available surgeon information. The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 20061030–35 New York: IEEE
    [Google Scholar]
65. 65.  Garcia-Ruiz A, Gagner M, Miller JH, Steiner CP, Hahn JF 1998. Manual versus robotically assisted laparoscopic surgery in the performance of basic manipulation and suturing tasks. Arch. Surg. 133:957–61
    [Google Scholar]
66. 66.  Wagner CR, Stylopoulos N, Howe RD 2002. The role of force feedback in surgery: analysis of blunt dissection. 10th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems68–74 New York: IEEE
    [Google Scholar]
67. 67.  Wagner CR, Stylopoulos N, Jackson PG, Howe RD 2007. The benefit of force feedback in surgery: examination of blunt dissection. Presence Teleoper. Virtual Environ. 16:252–62
    [Google Scholar]
68. 68.  Pillarisetti A, Pekarev M, Brooks AD, Desai JP 2006. Evaluating the role of force feedback for biomanipulation tasks. 2006 14th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems11–18 New York: IEEE
    [Google Scholar]
69. 69.  Tholey G, Desai JP, Castellanos AE 2003. Evaluating the role of vision and force feedback in minimally invasive surgery: new automated laparoscopic grasper and a case study. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2003 RE Ellis, TM Peters 198–205 Berlin: Springer
    [Google Scholar]
70. 70.  Kuchenbecker KJ, Gurari N, Okamura AM 2007. Quantifying the value of visual and haptic position feedback during force-based motion control. Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems561–62 New York: IEEE
    [Google Scholar]
71. 71.  Çavuolu MC, Tendick F, Cohn M, Sastry SS 1999. A laparoscopic telesurgical workstation. IEEE Trans. Robot. Autom. 15:728–39
    [Google Scholar]
72. 72.  Tadano K, Kawashima K 2006. Development of 4-DOFs forceps with force sensing using pneumatic servo system. 2006 IEEE International Conference on Robotics and Automation2250–55 New York: IEEE
    [Google Scholar]
73. 73.  Seibold U, Kubler B, Hirzinger G 2005. Prototype of instrument for minimally invasive surgery with 6-axis force sensing capability. 2005 IEEE International Conference on Robotics and Automation496–501 New York: IEEE
    [Google Scholar]
74. 74.  Ascari L, Stefanini C, Menciassi A, Sahoo S, Rabischong P, Dario P 2003. A new active microendoscope for exploring the sub-arachnoid space in the spinal cord. 2003 IEEE International Conference on Robotics and Automation 22657–62 New York: IEEE
    [Google Scholar]
75. 75.  Takahashi H, Warisawa S, Mitsuishi M, Arata J, Hashizume M 2006. Development of high dexterity minimally invasive surgical system with augmented force feedback capability. The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006284–89 New York: IEEE
    [Google Scholar]
76. 76.  Puangmali P, Althoefer K, Seneviratne LD, Murphy D, Dasgupta P 2008. State-of-the-art in force and tactile sensing for minimally invasive surgery. IEEE Sens. J. 8:371–81
    [Google Scholar]
77. 77.  Berkelman PJ, Whitcomb LL, Taylor RH, Jensen P 2003. A miniature microsurgical instrument tip force sensor for enhanced force feedback during robot-assisted manipulation. IEEE Trans. Robot. Autom. 19:917–21
    [Google Scholar]
78. 78.  Menciassi A, Eisinberg A, Carrozza MC, Dario P 2003. Force sensing microinstrument for measuring tissue properties and pulse in microsurgery. IEEE/ASME Trans. Mechatron. 8:10–17
    [Google Scholar]
79. 79.  Ottensmeyer MP, Salisbury JK 2001. In vivo data acquisition instrument for solid organ mechanical property measurement. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001975–82 Berlin: Springer
    [Google Scholar]
80. 80.  Peirs J, Clijnen J, Reynaerts D, Van Brussel H, Herijgers P et al. 2004. A micro optical force sensor for force feedback during minimally invasive robotic surgery. Sens. Actuators A 115:447–55
    [Google Scholar]
81. 81.  Puangmali P, Liu H, Althoefer K, Seneviratne LD 2008. Optical fiber sensor for soft tissue investigation during minimally invasive surgery. 2008 IEEE International Conference on Robotics and Automation2934–39 New York: IEEE
    [Google Scholar]
82. 82.  Kapoor A, Simaan N, Kazanzides P 2004. A system for speed and torque control of DC motors with application to small snake robots. Presented at IEEE Mechatron. Robot., Aachen, Ger., Sept. 13–15. http://www.cs.jhu.edu/∼kapoor/lopomoco/mechrob
83. 83.  Tholey G, Pillarisetti A, Green W, Desai J 2004. Design, development, and testing of an automated laparoscopic grasper with 3-D force measurement capability. Medical Simulation: International Symposium, ISMS 2004 S Cotin, D Metaxas 38–48 Berlin: Springer
    [Google Scholar]
84. 84.  Tholey G, Desai JP 2007. A modular, automated laparoscopic grasper with three-dimensional force measurement capability. 2007 IEEE International Conference on Robotics and Automation250–55 New York: IEEE
    [Google Scholar]
85. 85.  Wallace DT, Stahler G, Goldenberg A, Reis G, Younge RG et al. 2011. Method of sensing forces on a working instrument US Patent No. 8052621
    [Google Scholar]
86. 86.  Xu K, Simaan N 2008. An investigation of the intrinsic force sensing capabilities of continuum robots. IEEE Trans. Robot. 24:576–87
    [Google Scholar]
87. 87.  Leong F, Garbin N, Natali CD, Mohammadi A, Thiruchelvam D et al. 2016. Magnetic surgical instruments for robotic abdominal surgery. IEEE Rev. Biomed. Eng. 9:66–78
    [Google Scholar]
88. 88.  Cho YB, Park CM, Chun HK, Yi LJ, Park JH et al. 2011. Transvaginal endoscopic cholecystectomy using a simple magnetic traction system. Minim. Invasive Ther. Allied Technol. 20:174–8
    [Google Scholar]
89. 89.  Hu T, Allen PK, Hogle NJ, Fowler DL 2009. Insertable surgical imaging device with pan, tilt, zoom, and lighting. Int. J. Robot. Res. 28:1373–86
    [Google Scholar]
90. 90.  Park S, Bergs RA, Eberhart R, Baker L, Fernandez R, Cadeddu JA 2007. Trocar-less instrumentation for laparoscopy. Ann. Surg. 245:379–84
    [Google Scholar]
91. 91.  Cadeddu J, Fernandez R, Desai M, Bergs R, Tracy C et al. 2009. Novel magnetically guided intra-abdominal camera to facilitate laparoendoscopic single-site surgery: initial human experience. Surg. Endosc. Other Interv. Tech. 23:1894–99
    [Google Scholar]
92. 92.  Terry BS, Mills ZC, Schoen JA, Rentschler ME 2012. Single-port-access surgery with a novel magnet camera system. IEEE Trans. Biomed. Eng. 59:1187–93
    [Google Scholar]
93. 93.  Tortora G, Salerno M, Ranzani T, Tognarelli S, Dario P, Menciassi A 2013. A modular magnetic platform for natural orifice transluminal endoscopic surgery. 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)6265–68 New York: IEEE
    [Google Scholar]
94. 94.  Lehman AC, Wood NA, Farritor S, Goede MR, Oleynikov D 2011. Dexterous miniature robot for advanced minimally invasive surgery. Surg. Endosc. Other Interv. Tech. 25:119–23
    [Google Scholar]
95. 95.  Tortora G, Dario P, Menciassi A 2014. Array of robots augmenting the kinematics of endocavitary surgery. IEEE/ASME Trans. Mechatron. 19:1821–29
    [Google Scholar]
96. 96.  Tortora G, Valdastri P, Susilo E, Menciassi A, Dario P et al. 2009. Propeller-based wireless device for active capsular endoscopy in the gastric district. Minim. Invasive Ther. Allied Technol. 18:280–90
    [Google Scholar]
97. 97.  Brewer RD, Loewke KE, Duval EF, Salisbury JK 2008. Force control of a permanent magnet for minimally-invasive procedures. 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics580–86 New York: IEEE
    [Google Scholar]
98. 98.  Ikuta K, Makita S, Arimoto S 1991. Non-contact magnetic gear for micro transmission mechanism. Proceedings: IEEE Micro Electro Mechanical Systems: An Investigation of Micro Structures, Sensors, Actuators, Machines and Robots125–30 New York: IEEE
    [Google Scholar]
99. 99.  Leong F, Mohammadi A, Tan Y, Thiruchelvam D, Valdastri P, Oetomo D 2017. Magnetic interactions of neighbouring stator sets in multi DOF local electromagnetic actuation for robotic abdominal surgery. 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems5723–29 New York: IEEE
    [Google Scholar]
100. 100.  Di Natali C, Buzzi J, Garbin N, Beccani M, Valdastri P 2015. Closed-loop control of local magnetic actuation for robotic surgical instruments. IEEE Trans. Robot. 31:143–56
     [Google Scholar]
101. 101.  Mohammadi A, Samsonas D, Natali CD, Valdastri P, Tan Y, Oetomo D 2015. Speed control of non-collocated stator-rotor synchronous motor with application in robotic surgery. 2015 10th Asian Control Conference (ASCC) New York: IEEE https://doi.org/10.1109/ASCC.2015.7244830
     [Crossref] [Google Scholar]
102. 102.  Ciuti G, Menciassi A, Dario P 2011. Capsule endoscopy: from current achievments to open challenges. IEEE Rev. Biomed. Eng. 4:59–72
     [Google Scholar]
103. 103. Given Imaging. 2017. Pillcam capsule endoscopy http://www.givenimaging.com/en-int/Innovative-Solutions/Capsule-Endoscopy/Pages/default.aspx
     [Google Scholar]
104. 104.  Shamsudhin N, Zverev VI, Keller H, Pane S, Egolf PW et al. 2017. Magnetically guided capsule endoscopy. Med. Phys. 44:e91–111
     [Google Scholar]
105. 105.  Liu L, Towfighian S, Hila A 2015. A review of locomotion systems for capsule endoscopy. IEEE Rev. Biomed. Eng. 8:138–51
     [Google Scholar]
106. 106.  Woo SH, Kim TW, Mohy-Ud-Din Z, Park IY, Cho JH 2011. Small intestinal model for electrically propelled capsule endoscopy. BioMed. Eng. OnLine 10:108
     [Google Scholar]
107. 107.  Kim B, Park S, Park JO 2009. Microrobots for a capsule endoscope. 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics729–34 New York: IEEE
     [Google Scholar]
108. 108.  Valdastri P, Webster RJ, Quaglia C, Quirini M, Menciassi A, Dario P 2009. A new mechanism for mesoscale legged locomotion in compliant tubular environments. IEEE Trans. Robot. 25:1047–57
     [Google Scholar]
109. 109.  Martel S 2014. Advantages and limitations of the various magnetic manipulation methods of untethered agents in the human body. 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics13–18 New York: IEEE
     [Google Scholar]
110. 110.  Ciuti G, Donlin R, Valdastri P, Arezzo A, Menciassi A et al. 2010. Robotic versus manual control in magnetic steering of an endoscopic capsule. Endoscopy 42:148–52
     [Google Scholar]
111. 111.  Mehrtash M, Khamesee MB 2011. Design and implementation of LQG \LTR controller for a magnetic telemanipulation system-performance evaluation and energy saving. Microsyst. Technol. 17:1135–43
     [Google Scholar]
112. 112.  Mehrtash M, Khamesee MB, Tarao S, Tsuda N, Chang JY 2012. Human-assisted virtual reality for a magnetic-haptic micromanipulation platform. Microsyst. Technol. 18:1407–15
     [Google Scholar]
113. 113.  Mehrtash M, Zhang X, Khamesee MB 2015. Bilateral magnetic micromanipulation using off-board force sensor. IEEE/ASME Trans. Mechatron. 20:3223–31
     [Google Scholar]
114. 114.  Pan G, Wang L 2012. Swallowable wireless capsule endoscopy: progress and technical challenges. Gastroenterol. Res. Pract. 2012:841691
     [Google Scholar]
115. 115.  Than TD, Alici G, Zhou H, Li W 2012. A review of localization systems for robotic endoscopic capsules. IEEE Trans. Biomed. Eng. 59:2387–99
     [Google Scholar]
116. 116.  Hu C, Li M, Song S, Yang W, Zhang R, Meng MQH 2010. A cubic 3-axis magnetic sensor array for wirelessly tracking magnet position and orientation. IEEE Sens. J. 10:903–13
     [Google Scholar]
117. 117.  Song S, Li B, Qiao W, Hu C, Ren H et al. 2014. 6-D magnetic localization and orientation method for an annular magnet based on a closed-form analytical model. IEEE Trans. Magnet. 50:1–11
     [Google Scholar]
118. 118.  Aziz SM, Grcic M, Vaithianathan T 2008. A real-time tracking system for an endoscopic capsule using multiple magnetic sensors. Smart Sensors and Sensing Technology SC Mukhopadhyay, GS Gupta 201–18 Berlin: Springer
     [Google Scholar]
119. 119.  Popek KM, Mahoney AW, Abbott JJ 2013. Localization method for a magnetic capsule endoscope propelled by a rotating magnetic dipole field. 2013 IEEE International Conference on Robotics and Automation5348–53 New York: IEEE
     [Google Scholar]
120. 120.  Yim S, Sitti M 2013. 3-D localization method for a magnetically actuated soft capsule endoscope and its applications. IEEE Trans. Robot. 29:1139–51
     [Google Scholar]
121. 121.  Di Natali C, Beccani M, Valdastri P 2013. Real-time pose detection for magnetic medical devices. IEEE Trans. Magnet. 49:3524–27
     [Google Scholar]
122. 122.  Natali CD, Beccani M, Simaan N, Valdastri P 2015. Jacobian-based iterative method for magnetic localization in robotic capsule endoscopy. IEEE Trans. Robot. 2:327–38
     [Google Scholar]
123. 123.  Nelson BJ, Kaliakatsos IK, Abbott JJ 2010. Microrobots for minimally invasive medicine. Annu. Rev. Biomed. Eng. 12:55–85
     [Google Scholar]
124. 124.  Sitti M, Ceylan H, Hu W, Giltinan J, Turan M et al. 2015. Biomedical applications of untethered mobile milli/microrobots. Proc. IEEE 103:205–24
     [Google Scholar]
125. 125.  Bogue R 2008. The development of medical microrobots: a review of progress. Ind. Robot 35:294–99
     [Google Scholar]
126. 126.  Miyashita S, Guitron S, Yoshida K, Li S, Damian DD, Rus D 2016. Ingestible, controllable, and degradable origami robot for patching stomach wounds. 2016 IEEE International Conference on Robotics and Automation909–16 New York: IEEE
     [Google Scholar]
127. 127.  Hosney A, Abdalla J, Amin IS, Hamdi N, Khalil ISM 2016. In vitro validation of clearing clogged vessels using microrobots. 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)272–77 New York: IEEE
     [Google Scholar]
128. 128.  Kummer MP, Abbott JJ, Kratochvil BE, Borer R, Sengul A, Nelson BJ 2010. Octomag: an electromagnetic system for 5-DOF wireless micromanipulation. IEEE Trans. Robot. 26:1006–17
     [Google Scholar]
129. 129.  Martel S 2013. Microrobotics in the vascular network: present status and next challenges. J. Micro-Bio Robot. 8:41–52
     [Google Scholar]
130. 130.  Diller E 2011. Micro-Scale Mobile Robotics Found. Trends Robot. Vol. 2, No. 3 Boston: Now
     [Google Scholar]
131. 131.  Yip MC, Camarillo DB 2014. Model-less feedback control of continuum manipulators in constrained environments. IEEE Trans. Robot. 30:880–89
     [Google Scholar]
132. 132.  Taylor R, Jensen P, Whitcomb L, Barnes A, Kumar R et al. 1999. A steady-hand robotic system for microsurgical augmentation. Int. J. Robot. Res. 18:1201–10
     [Google Scholar]
133. 133.  Jakopec M, Rodriguez y Baena F, Harris SJ, Gomes P, Cobb J, Davies BL 2003. The hands-on orthopaedic robot “acrobot”: early clinical trials of total knee replacement surgery. IEEE Trans. Robot. Autom. 19:902–11
     [Google Scholar]
134. 134.  Rosenberg LB 1993. Virtual fixtures as tools to enhance operator performance in telepresence environments. Telemanipulator Technology and Space Telerobotics10–21 Bellingham, WA: SPIE
     [Google Scholar]
135. 135.  Perri MT, Trejos AL, Naish MD, Patel RV, Malthaner RA 2010. Initial evaluation of a tactile/kinesthetic force feedback system for minimally invasive tumor localization. IEEE/ASME Trans. Mechatron. 15:925–31
     [Google Scholar]
136. 136.  Tholey G, Desai JP, Castellanos AE 2005. Force feedback plays a significant role in minimally invasive surgery: results and analysis. Ann. Surg. 241:102–9
     [Google Scholar]
137. 137.  Okamura AM 2009. Haptic feedback in robot-assisted minimally invasive surgery. Curr. Opin. Urol. 19:102
     [Google Scholar]
138. 138.  Haraguchi D, Tadano K, Kawashima K 2011. A prototype of pneumatically-driven forceps manipulator with force sensing capability using a simple flexible joint. 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems931–36 New York: IEEE
     [Google Scholar]
139. 139.  Rucker DC, Webster RJ 2011. Deflection-based force sensing for continuum robots: a probabilistic approach. 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems3764–69 New York: IEEE
     [Google Scholar]
140. 140.  Wei W, Simaan N 2012. Modeling, force sensing, and control of flexible cannulas for microstent delivery. J. Dyn. Syst. Meas. Control 134:041004
     [Google Scholar]
141. 141.  Baki P, Székely G, Kósa G 2013. Design and characterization of a novel, robust, tri-axial force sensor. Sens. Actuators A 192:101–10
     [Google Scholar]
142. 142.  Reiter A, Allen PK 2010. An online learning approach to in-vivo tracking using synergistic features. 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems3441–46 New York: IEEE
     [Google Scholar]
143. 143.  Baumann M, Léonard S, Croft EA, Little JJ 2010. Path planning for improved visibility using a probabilistic road map. IEEE Trans. Robot. 26:195–200
     [Google Scholar]
144. 144.  Léonard S, Croft EA, Little JJ 2009. Planning collision-free and occlusion-free paths for industrial manipulators with eye-to-hand configuration. 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems5083–88 New York: IEEE
     [Google Scholar]
145. 145.  Chalasani P, Wang L, Roy R, Simaan N, Taylor RH, Kobilarov M 2016. Concurrent nonparametric estimation of organ geometry and tissue stiffness using continuous adaptive palpation. 2016 IEEE International Conference on Robotics and Automation4164–71 New York: IEEE
     [Google Scholar]
146. 146.  Wang L, Chen Z, Chalasani P, Yasin RM, Kazanzides P et al. 2017. Force-controlled exploration for updating virtual fixture geometry in model-mediated telemanipulation. J. Mech. Robot. 9:021010
     [Google Scholar]
147. 147.  Ayvali E, Srivatsan RA, Wang L, Roy R, Simaan N, Choset H 2016. Using Bayesian optimization to guide probing of a flexible environment for simultaneous registration and stiffness mapping. 2016 IEEE International Conference on Robotics and Automation931–36 New York: IEEE
     [Google Scholar]
148. 148.  Pile J, Wanna GB, Simaan N 2014. Force-based flexible path plans for robotic electrode insertion. 2014 IEEE International Conference on Robotics and Automation297–303 New York: IEEE
     [Google Scholar]
149. 149.  Miga MI, Sinha TK, Cash DM, Galloway RL, Weil RJ 2003. Cortical surface registration for image-guided neurosurgery using laser-range scanning. IEEE Trans. Med. Imaging 22:973–85
     [Google Scholar]
150. 150.  Burgner J, Simpson A, Fitzpatrick J, Lathrop R, Herrell S et al. 2013. A study on the theoretical and practical accuracy of conoscopic holography-based surface measurements: toward image registration in minimally invasive surgery. Int. J. Med. Robot. Comput. Assist. Surg. 9:190–203
     [Google Scholar]
151. 151.  Hayashibe M, Suzuki N, Nakamura Y 2006. Laser-scan endoscope system for intraoperative geometry acquisition and surgical robot safety management. Med. Image Anal. 10:509–19
     [Google Scholar]