Hostname: page-component-6bb9c88b65-spzww Total loading time: 0 Render date: 2025-07-25T02:18:56.309Z Has data issue: false hasContentIssue false

A compact remote center of motion mechanism based on the coupling of three rotations realized by nonlinear transmission

Published online by Cambridge University Press:  25 July 2025

Haixin Zhao
Affiliation:
School of Mechanical Engineering, Tianjin University, Tianjin, China
Jinhua Li*
Affiliation:
School of Mechanical Engineering, Tianjin University, Tianjin, China
Yue Yu
Affiliation:
School of Mechanical Engineering, Tianjin University, Tianjin, China
Jianchang Zhao*
Affiliation:
National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
*
Corresponding authors: Jinhua Li; Email: lijinhua@tju.edu.cn, Jianchang Zhao; Email: jianchangzhao@mail.tsinghua.edu.cn
Corresponding authors: Jinhua Li; Email: lijinhua@tju.edu.cn, Jianchang Zhao; Email: jianchangzhao@mail.tsinghua.edu.cn

Abstract

The remote center of motion (RCM) mechanism is one of the key components of minimally invasive surgical robots. Nevertheless, the most widely used parallelogram-based RCM mechanism tends to have a large footprint, thereby increasing the risk of collisions between the robotic arms during surgical procedures. To solve this problem, this study proposes a compact RCM mechanism based on the coupling of three rotational motions realized by nonlinear transmission. Compared to the parallelogram-based RCM mechanism, the proposed design offers a smaller footprint, thereby reducing the risk of collisions between the robotic arms. To address the possible errors caused by the elasticity of the transmission belts, an error model is established for the transmission structure that includes both circular and non-circular pulleys. A prototype is developed to verify the feasibility of the proposed mechanism, whose footprint is further compared with that of the parallelogram-based RCM mechanism. The results indicate that our mechanism satisfies the constraints of minimally invasive surgery, provides sufficient stiffness, and exhibits a more compact design. The current study provides a new direction for the miniaturization design of robotic arms in minimally invasive surgical robots.

Information

Type
Research Article
Copyright
© The Author(s), 2025. Published by Cambridge University Press

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.)

Article purchase

Temporarily unavailable

References

Dai, J. S., “Surgical robotics and its development and progress,” Robotica 28(2), 161161 (2010).CrossRefGoogle Scholar
Satava, R. M., “Robotics, telepresence and virtual reality: A critical analysis of the future of surgery,” Minim. Invasiv. Ther. 1(6), 357363 (1992).Google Scholar
Kuo, C. H., Dai, J. S. and Dasgupta, P., “Kinematic design considerations for minimally invasive surgical robots: An overview,” Int. J. Med. Robot. Comput. Assist. Surg. 8(2), 127145 (2012).CrossRefGoogle ScholarPubMed
Zong, G., Pei, X., Yu, J. and Bi, S., “Classification and type synthesis of 1-DOF remote center of motion mechanisms,” Mech. Mach. Theory 43(12), 15851595 (2008).CrossRefGoogle Scholar
Aghakhani, N., Geravand, M., Shahriari, N., Vendittelli, M. and Oriolo, G., “Task Control with Remote Center of Motion Constraint for Minimally Invasive Robotic Surgery,” In: Proceedings of 2013 IEEE International Conference on Robotics and Automation, Karlsruhe, Germany (IEEE, 2013) pp. 58075812.CrossRefGoogle Scholar
Khan, A. T. and Li, S., “Smart surgical control under RCM constraint using bio-inspired network,” Neurocomputing 470, 121129 (2022).CrossRefGoogle Scholar
Khan, A. H., Li, S. and Cao, X., “Tracking control of redundant manipulator under active remote center-of-motion constraints: An RNN-based metaheuristic approach,” Sci. China Inform. Sci. 64(3), 118 (2021).CrossRefGoogle Scholar
Khan, A. H., Li, S., Chen, D. and Liao, L., “Tracking control of redundant mobile manipulator: An RNN based metaheuristic approach,” Neurocomputing 400, 272284 (2020).CrossRefGoogle Scholar
Khan, A. H., Li, S. and Luo, X., “Obstacle avoidance and tracking control of redundant robotic manipulator: An RNN-based metaheuristic approach,” IEEE Trans. Ind. Inf. 16(7), 46704680 (2019).CrossRefGoogle Scholar
Taylor, R. H. and Stoianovici, D., “Medical robotics in computer-integrated surgery,” IEEE Trans. Robot. Autom. 19(5), 765781 (2003).CrossRefGoogle Scholar
Locke, R. C. O. and Patel, R. V., “Optimal Remote Center-of-Motion Location for Robotics-assisted Minimally-invasive Surgery,” In: Proceedings of the IEEE International Conference on Robotics and Automation, Rome, Italy (IEEE, 2007) pp. 19001905.CrossRefGoogle Scholar
Beira, R., Santos-Carreras, L., Rognini, G., Bleuler, H. and Clavel, R., “Dionis: A novel remote-center-of-motion parallel manipulator for minimally invasive surgery,” Appl. Bionics Biomech. 8(2), 191208 (2011).CrossRefGoogle Scholar
Kuo, C. H. and Dai, J. S., “Kinematics of a fully decoupled remote center-of-motion parallel manipulator for minimally invasive surgery,” J. Med. Devices 6(2), 021008 (2012).CrossRefGoogle Scholar
Chen, G., Wang, J., Wang, H., Chen, C., Parenti-Castelli, V. and Angeles, J., “Design and validation of a spatial two-limb 3R1T parallel manipulator with remote center-of-motion,” Mech. Mach. Theory 149, 103807 (2020).CrossRefGoogle Scholar
Bian, Y., Zhao, J. C., Li, J. H., Wei, G. W. and Li, J. M., “A class of spatial remote center-of-motion mechanisms and its forward kinematics,” Robotica 41(3), 885899 (2023).CrossRefGoogle Scholar
Li, L., Tian, C., Xia, Z. and Zhang, D., “Optimal design of a generalized single-loop parallel manipulator with RCM characteristic considering motion/force transmissibility,” Robotica 43(3), 117 (2025).CrossRefGoogle Scholar
Li, J. M., Zhang, G. K., Xing, Y., Liu, H. B. and Wang, S. X., “A class of 2-degree-of-freedom planar remote center-of-motion mechanisms based on virtual parallelograms,” J. Mech. Robot. 6(3), 031014 (2014).CrossRefGoogle Scholar
Huang, L., Yang, Y., Xiao, J. J. and Su, P., “Type synthesis of 1R1T remote center of motion mechanisms based on pantograph mechanisms,” J. Mech. Des. 138(1), 014501 (2016).Google Scholar
Chen, G., Wang, J. and Wang, H., “A new type of planar two degree-of-freedom remote center-of-motion mechanism inspired by the Peaucellier-lipkin straight-line linkage,” J. Mech. Des. 141(1), 19 (2019).CrossRefGoogle Scholar
Kuo, C. H. and Dai, J. S., “Robotics for Minimally Invasive Surgery: A Historical Review from the Perspective of Kinematics,” In: International Symposium on History of Machines and Mechanisms: Proceedings of HMM 2008 (Springer, 2009) pp. 337354.CrossRefGoogle Scholar
Hong, D. W. and Cipra, R. J., “A method for representing the configuration and analyzing the motion of complex cable-pulley systems,” J. Mech. Des. 125(2), 332341 (2003).CrossRefGoogle Scholar
Liu, S. T., Harewood, L., Chen, B. and Chen, C., “A skeletal prototype of surgical arm based on dual-triangular mechanism,” J. Mech. Robot. 8(4), 041015 (2016).CrossRefGoogle Scholar
Liu, S., Chen, B., Caro, S., Briot, S., Harewood, L. and Chen, C., “A cable linkage with remote centre of motion,” Mech. Mach. Theory 105, 583605 (2016).CrossRefGoogle Scholar
He, Y., Zhang, P., Jin, H., Hu, Y. and Zhang, J., “Type synthesis for remote center of motion mechanisms based on coupled motion of two degrees-of-freedom,” J. Mech. Des. 138(12), 122301 (2016).CrossRefGoogle Scholar
Kawamura, S., Choe, W., Tanaka, S. and Pandian, S. R., “Development of an Ultrahigh Speed Robot FALCON Using Wire Drive System,” In: IEEE International Conference on Robotics and Automation (IEEE, 1995) pp. 215220.CrossRefGoogle Scholar
Schmidt, V., Kraus, W. and Pott, A., “Presentation of Experimental Results on Stability of a 3 DOF 4-Cable-driven Parallel Robot Without Constraints,” In: Cable-Driven Parallel Robots: Proceedings of the Second International Conference on Cable-Driven Parallel Robots, Berlin, Germany (Springer, 2014) pp. 8799.CrossRefGoogle Scholar
Lozzi, A., “Non-circular gears—graphic generation of involutes and base outlines,” Proc. Inst. Mech. Eng., Part C: J. Mech. Eng. Sci. 214(3), 411422 (2000).CrossRefGoogle Scholar
Nai, T. Y., Herder, J. L. and Tuijthof, G. J., “Steerable mechanical joint for high load transmission in minimally invasive instruments,” J. Med. Devices 5(3), 034503 (2011).CrossRefGoogle Scholar
Nelson, T. G., Lang, R. J., Magleby, S. P. and Howell, L. L., “Curved-folding-inspired deployable compliant rolling-contact element (D-CORE),” Mech. Mach. Theory 96, 225238 (2016).CrossRefGoogle Scholar
Suh, J. W. and Kim, K. Y., “Harmonious cable actuation mechanism for soft robot joints using a pair of noncircular pulleys,” J. Mech. Robot. 10(6), 061002 (2018).CrossRefGoogle Scholar
Li, J. H., Yu, Y., Bai, Y. T., Cai, C. C., Hao, X. Q. and Zhao, J. C., “Development of a cam-based minimally invasive surgical instrument with reduced backlash,” Int. J. Med. Rob. Comput. Assisted Surg. 21(2), e70063 (2025).CrossRefGoogle ScholarPubMed
Rosen, J., Brown, J. D., Chang, L., Barreca, M., Sinanan, M. and Hannaford, B., “The BlueDRAGON-A System for Measuring the Kinematics and Dynamics of Minimally Invasive Surgical Tools In-vivo,” In: Proceedings 2002 IEEE International Conference on Robotics and Automation, Arlington, VA (IEEE, 2002) pp. 18761881.CrossRefGoogle Scholar
Rosen, J., Brown, J. D., Chang, L., Sinanan, M. N. and Hannaford, B., “Generalized approach for modeling minimally invasive surgery as a stochastic process using a discrete Markov model,” IEEE Trans. Biomed. Eng. 53(3), 399413 (2006).CrossRefGoogle ScholarPubMed
Huang, L., Yin, L., Liu, B. and Yang, Y., “Design and error evaluation of planar 2DOF remote center of motion mechanisms with cable transmissions,” J. Mech. Des. 143(1), 013301 (2021).CrossRefGoogle Scholar
Zhang, H. F., Li, J. M., Kong, K. and Wang, S. X., “System design of a novel minimally invasive surgical robot that combines the advantages of MIS techniques and robotic technology,” IEEE Access 8, 4114741161 (2020).CrossRefGoogle Scholar
Chung, D. G., Hwang, M., Cheon, B., Kong, D., Kang, D., Lee, D. H., Kim, C. K., Kim, D., Han, J. M., Kim, Y. G. and Kwon, D. S., “Bed-mounted laparoscopic surgical robot system with novel positioning arm mechanism,” Int. J. Med. Rob. Comput. Assisted Surg. 18(4), e2402 (2022).CrossRefGoogle ScholarPubMed
Ferguson, J. M., Cai, L. Y., Reed, A., Siebold, M., De, S., Herrell, S. D. and Webster, R. J., “Toward Image-guided Partial Nephrectomy with the Da Vinci Robot: Exploring Surface Acquisition Methods for Intraoperative Re-registration,” In: Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling (Houston, TX, 2018) pp. 4959.Google Scholar
Peirs, J., Clijnen, J., Reynaerts, D., Van Brussel, H., Herijgers, P., Corteville, B. and Boone, S., “A micro optical force sensor for force feedback during minimally invasive robotic surgery,” Sens. Actuators A: Phys. 115(2-3), 447455 (2004).CrossRefGoogle Scholar
Hong, M. B. and Jo, Y. H., “Design and evaluation of 2-DOF compliant forceps with force-sensing capability for minimally invasive robot surgery,” IEEE Trans. Robot. 28(4), 932941 (2012).CrossRefGoogle Scholar