Hostname: page-component-76fb5796d-r6qrq Total loading time: 0 Render date: 2024-04-25T17:56:52.968Z Has data issue: false hasContentIssue false
  • English
  • Français

Dimensional synthesis and concept design of a novel minimally invasive surgical robot

Published online by Cambridge University Press:  29 January 2018

Guojun Niu ,
Bo Pan ,
Fuhai Zhang ,
Haibo Feng ,
Wenpeng Gao  and
Yili Fu
Guojun Niu
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, Heilongjiang, P.R. of China E-mail: 11b908015@hit.edu.cn, zfhhit@hit.edu.cn, Fenghaibo777@163.com
Bo Pan*
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, Heilongjiang, P.R. of China E-mail: 11b908015@hit.edu.cn, zfhhit@hit.edu.cn, Fenghaibo777@163.com
Fuhai Zhang
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, Heilongjiang, P.R. of China E-mail: 11b908015@hit.edu.cn, zfhhit@hit.edu.cn, Fenghaibo777@163.com
Haibo Feng
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, Heilongjiang, P.R. of China E-mail: 11b908015@hit.edu.cn, zfhhit@hit.edu.cn, Fenghaibo777@163.com
Wenpeng Gao
Affiliation:
School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, P.R. of China E-mail: wpgao@hit.edu.cn
Yili Fu*
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, Heilongjiang, P.R. of China E-mail: 11b908015@hit.edu.cn, zfhhit@hit.edu.cn, Fenghaibo777@163.com
*
*Corresponding authors. E-mail: mepanbo@hit.edu.cn, biorobfu@126.com
*Corresponding authors. E-mail: mepanbo@hit.edu.cn, biorobfu@126.com
Get access Rights & Permissions [Opens in a new window]

Summary

A new minimally invasive surgical (MIS) robot consisting of a spherical remote center motion (RCM) mechanism with modular design is proposed. A multi-objective dimensional synthesis model is presented to obtain the excellent performance indices. There are four objectives: a global kinematic index, a compactness index, a global comprehensive stiffness index, and a global dynamic index. Other indices characterizing the design requirement, such as workspace, mechanical parameter, and mass, are chosen as constraints. A new decoupled mechanism is raised to solve the coupled motion between the linear platform and the four degrees of freedom (DoF) of surgical instrument as a result of post-driving motors. Another new mechanical decoupled method is proposed to eliminate the coupled motion between the wrist and the forceps, enhance the dexterity of surgical instrument, and improve the independence of each motor. Then, a 7-DoF MIS robotic prototype based on optimization results has been built up. Experiment results validate the effectiveness of the two mechanical decoupled methods. The position change of the RCM point, accuracy, and repeatability of the MIS robot meet the requirements of MIS. Successful animal experiments validate the effectiveness of the novel MIS robot.

Keywords

Minimally invasive surgeryDimensional synthesisMulti-objective optimizationRCMDecoupled motion
Type
Articles
Information
Robotica , Volume 36 , Issue 5 , May 2018 , pp. 715 - 737
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Navarro, J. S., Garcia, N., Perez, C., Fernandez, E., Saltaren, R. and Almonacid, M., “Kinematics of a robotic 3UPS1S spherical wrist designed for laparoscopic applications,” Int. J. Med. Robot. Comput. Assist. Surg. 6 (3), 291–300 (2010).Google Scholar
2. Puglisi, L. J., Saltaren, R. J., Portolés, G. R., Moreno, H., Cárdenas, P. F. and Garcia, C., “Design and kinematic analysis of 3PSS-1S wrist for needle insertion guidance,” Robot. Auton. Syst. 61 (5), 417–427 (2013).Google Scholar
3. Kuo, C. and Dai, J. S., “Kinematics of a fully-decoupled remote center-of-motion parallel manipulator for minimally invasive surgery,” J. Med. Devices 6 (2), 21008-1–21008-12 (2012).Google Scholar
4. Chen, C. and Harewood, L., “Novel Linkage with Remote Center of Motion,” Proceedings of the 3rd IFToMM International Symposium on Robotics and Mechatronics, Singapore (2–4 October, 2013) pp. 1–4.Google Scholar
5. Bai, G., Li, D., Wei, S. and Liao, Q., “Kinematics and synthesis of a type of mechanisms with multiple remote centers of motion,” Proc. Inst. Mech. Eng. C: J. Mech. Eng. Sci. 228 (18), 3430–3440 (2014).Google Scholar
6. Pisla, D., Gherman, B., Vaida, C. and Plitea, N., “Kinematic modeling of a 5-DOF hybrid parallel robot for laparoscopic surgery,” Robotica 30 (7), 1095–1107 (2012).Google Scholar
7. Vaida, C., Pisla, D., Plitea, N., Gherman, B., Gyurka, B., Graur, F. and Vlad, L., “Development of a Voice Controlled Surgical Robot,” In: New Trends in Mechanism Science (Viadero, F. and Ceccarelli, M., eds.) (Springer Dordrecht, 2010) pp. 567–574.Google Scholar
8. Herman, B., Dehez, B., Duy, K. T., Raucent, B., Dombre, E. and Krut, S., “Design and preliminary in vivo validation of a robotic laparoscope holder for minimally invasive surgery,” Int. J. Med. Robot. Comput. Assist. Surg. 5 (3), 319–326 (2009).Google Scholar
9. Ghodousssi, M., Butner, S. E. and Wang, Y., “Robotic Surgery—The Transatlantic Case,” Proceedings of the 2002 IEEE International Conference on Robotics and Automation, Washington, DC, USA (11–15 May, 2002) pp. 1882–1888.Google Scholar
10. Kim, S. K., Shin, W. H., Ko, S. Y., Kim, J. and Kwon, D. S., “Design of a Compact 5-DoF Surgical Robot of a Spherical Mechanism: CURES,” Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Xi'an China (2–5 July, 2008) pp. 990–995.Google Scholar
11. Madhani, A. J.., Niemeyer, G. and Salisbury, J. K., “The Black Falcon: A Teleoperated Surgical Instrument for Minimally Invasive Surgery,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Victoria, BC, Canada (17 October, 1998) pp. 936–944.Google Scholar
12. Guthart, G. and Salisbury, J. K., “The IntuitiveTM Telesurgery System: Overview and Application,” Proceedings of the IEEE International Conference on Robotics and Automation, San Francisco, CA, USA (24–28 April, 2000) pp. 618–621.Google Scholar
13. Rininsland, H., “ARTEMIS: A telemanipulator for cardiac surgery,” Eur. J. Cardio-Thorac. 16 (S2), S106–S111 (1999).Google Scholar
14. Kong, K., Li, J., Zhang, H., Li, J. and Wang, S., “Kinematic design of a generalized double parallelogram based remote center-of-motion mechanism for minimally invasive surgical robot,” J. Med. Devices 10 (4), 041006-1–041006-8 (2016).CrossRefGoogle Scholar
15. Yu, L., Wang, Z., Sun, L., Wang, W., Wang, L. and Du, Z., “A new forecasting kinematic algorithm of automatic navigation for a laparoscopic minimally invasive surgical robotic system,” Robotica 35 (5), 1192–1222 (2017).Google Scholar
16. Kang, H. and Wen, J. T., “Robotic assistants aid surgeons during minimally invasive procedures,” IEEE Eng. Med. Biol. 20 (1), 94–104 (2001).Google Scholar
17. Wang, S., Li, Q., Ding, J. and Zhang, Z., “Kinematic Design for Robot-Assisted Laryngeal Surgery Systems,” Proceeding of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China (9–15 October, 2006) pp. 2864–2869.Google Scholar
18. Vaida, C., Gherman, B., Pisla, D. and Plitea, N., “A CT-scan compatible robotic device for needle placement in medical applications,” Adv. Eng. Forum 8 (9), 574–583 (2013).Google Scholar
19. Lum, M. J., Rosen, J., Sinanan, M. N. and Hannaford, B., “Optimization of a spherical mechanism for a minimally invasive surgical robot: Theoretical and experimental approaches,” IEEE Trans. Bio-Med. Eng. 53 (7), 1440–1445 (2006).Google Scholar
20. Berkelman, P. and Ma, J., “A compact modular teleoperated robot system for laparoscopic surgery,” Int. J. Robot. Res. 28 (9), 119–1215 (2009).Google Scholar
21. Hannaford, B., Rosen, J., Friedman, D. W., King, H., Roan, P., Cheng, L., Glozman, D., Ma, J., Kosari, S. N. and White, L., “Raven-II: An open platform for surgical robotics research,” IEEE Trans. Bio-Med. Eng. 60 (4), 954–959 (2013).Google Scholar
22. Lum, M. J., Friedman, D. C., Sankaranarayanan, G., King, H., Fodero, K., Leyschke, R., Hannaford, B., Rosen, J. and Sinanan, M. N., “The RAVEN: Design and validation of a telesurgery system,” Int. J. Robot. Res. 28 (9), 183–1197 (2009).Google Scholar
23. Merlet, J. P., “Optimal Design for the Micro Parallel Robot MIPS,” Proceedings of the IEEE International Conference on Robotics and Automation, Washington, DC, USA (20–21 May, 2002) pp. 1149–1154.Google Scholar
24. Shin, W. H. and Kwon, D. S., “Surgical robot system for single-port surgery with novel joint mechanism,” IEEE Trans. Bio-Med. Eng. 60 (4), 937–944 (2013).Google Scholar
25. Piccigallo, M., Scarfogliero, U., Quaglia, C., Petroni, G., Valdastri, P., Menciassi, A. and Dario, P., “Design of a novel bimanual robotic system for single-port laparoscopy,” IEEE-ASM Trans. Mech. 15 (5), 871–878 (2010).Google Scholar
26. Feng, M., Fu, Y. L., Pan, B. and Zhao, X., “An improved surgical instrument without coupled motions that can be used in robotic-assisted minimally invasive surgery,” Proc. Inst. Mech. Eng. H 226 (8), 623–630 (2012).Google Scholar
27. Feng, M., Fu, Y. L., Pan, B. and Li, C., “Development of a medical robot system for minimally invasive surgery,” Int. J. Med. Robot. Comput. Assist. Surg. 8 (1), 85–96 (2012).Google Scholar
28. Nouaille, L., Vieyres, P. and Poisson, G., “Process of optimisation for a 4 DoF tele-echography robot,” Robotica 30 (07), 1131–1145 (2012).Google Scholar
29. Nouaille, L., Smith-Guérin, N., Poisson, G. and Arbeille, P., “Optimization of a 4 dof Tele-Echography Robot,” Proceeding of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan (18–22 October, 2010) pp. 3501–3506.Google Scholar
30. Zhang, X. and Nelson, C. A., “Multiple-criteria kinematic optimization for the design of spherical serial mechanisms using genetic algorithms,” J. Mech. Des. 133 (1), 011005-1–011005-11 (2011).Google Scholar
31. Zhang, P., Yao, Z. and Du, Z., “Global performance index system for kinematic optimization of robotic mechanism,” J. Mech. Des. 136 (3), 031001-1–0310012 (2014).Google Scholar
32. Kelaiaia, R., Company, O. and Zaatri, A., “Multiobjective optimization of a linear Delta parallel robot,” Mech. Mach. Theory 50, 159–178 (2012).Google Scholar
33. Gosselin, C. and Angeles, J., “A global performance index for the kinematic optimization of robotic manipulators,” J. Mech. Des. 113 (3), 220–226 (1991).Google Scholar
34. Nagai, K. and Liu, Z., “A Systematic Approach to Stiffness Analysis of Parallel Mechanisms,” Proceeding of the IEEE International Conference on Robotics and Automation, Pasadena, CA, USA (19–23 May, 2008) pp. 1543–1548.Google Scholar
35. Ganesh, S. S., Rao, A. B. K. and Darvekar, S., “Multi-objective optimization of a 3-DoF translational parallel kinematic machine,” J. Mech. Sci. Technol. 27 (12), 3797–3804 (2013).Google Scholar
36. Angeles, J. and Lpez-Cajun, C. S., “Kinematic isotropy and the conditioning index of serial robotic manipulators,” Int. J. Robot. Res. 11 (6), 560–571 (1992).Google Scholar
37. Kurazume, R. and Hasegawa, T., “A new index of serial-link manipulator performance combining dynamic manipulability and manipulating force ellipsoids,” IEEE Trans. Robot. 22 (5), 1022–1028 (2006).Google Scholar
38. Zhao, Y., “Dynamic optimum design of a three translational degrees of freedom parallel robot while considering anisotropic property,” Robot. Comput.-Integr. Manuf. 29 (4), 100–112 (2013).Google Scholar
39. Lampinen, J., “Multiobjective nonlinear Pareto-optimization,” Pre-investigation report (Lappeenranta University of Technology, Laboratory of Information Processing, Lapperanta, Finland, 2000).Google Scholar
40. Deb, K., Pratap, A., Agarwal, S. and Meyarivan, T., “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE Trans. Evol. Comput. 6 (2), 182–197 (2002).Google Scholar
41. Ur-rehman, R., Caro, S., Chablat, D. and Wenger, P., “Multi-objective path placement optimization of parallel kinematics machines based on energy consumption, shaking forces and maximum actuator torques application to the orthoglide,” Mech. Mach. Theory 45 (8), 1125–1141 (2010).Google Scholar
42. Gao, Z. and Zhang, D., “Performance analysis, mapping and multi-objective optimization of a hybrid robotic machine tool,” IEEE Trans. Ind. Electron. 62 (1), 423–433 (2014).Google Scholar
43. Brethé, J.F., Vasselin, E., Lefebvre, D. and Dakyo, B., “Modelling of repeatability phenomena using the stochastic ellipsoid approach,” Robotica 24 (04), 477–490 (2006).Google Scholar
44. Hijazi, A., Brethé, J. F. and Lefebvre, D., “Design of an XY-theta platform held by a planar manipulator with four revolute joints and evaluation of its precision performances,” Robotica 34 (11), 2532–2545 (2016).CrossRefGoogle Scholar