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Accurate kinematic and stiffness analysis of parallel cable-driven upper limb rehabilitation robot with spherical guide wheel cable-guiding mechanism

Published online by Cambridge University Press:  10 January 2025

Yupeng Zou*
Affiliation:
College of Mechanical and Electrical Engineering, China University of Petroleum (East China), Qingdao, China
Keyu Pan
Affiliation:
College of Mechanical and Electrical Engineering, China University of Petroleum (East China), Qingdao, China
Mengfei Wang
Affiliation:
College of Mechanical and Electrical Engineering, China University of Petroleum (East China), Qingdao, China
Xiaojing Lai
Affiliation:
College of Mechanical and Electrical Engineering, China University of Petroleum (East China), Qingdao, China
Tianyu Lan
Affiliation:
College of Mechanical and Electrical Engineering, China University of Petroleum (East China), Qingdao, China
Zhishen Zhou
Affiliation:
College of Mechanical and Electrical Engineering, China University of Petroleum (East China), Qingdao, China
Changsheng Li
Affiliation:
College of Mechanical and Electrical Engineering, China University of Petroleum (East China), Qingdao, China
*
Corresponding author: Yupeng Zou; Email: [email protected]

Abstract

Cable-guiding mechanisms (CGMs) and the stiffness characteristics directly influence the dynamic features of the cable-driven upper limb rehabilitation robot (PCUR), which will affect PCUR’s performance. This paper introduces a novel CGM design. Given the precision and movement stability considerations of the mechanism, an analytical model is developed. Using this model, we analyze the error of the CGM and derive velocity and acceleration mappings from the moving platform to the cables. Continuity of cable trajectory and tension is rigorously demonstrated. Subsequently, a mathematical model for PCUR stiffness is formulated. Utilizing MATLAB/Simscape Multibody, simulation models for the CGM and stiffness characteristics are constructed. The feasibility of the proposed CGM design is validated through simulation and experimentation, while the influence of stiffness characteristics on PCUR motion stability is comprehensively analyzed.

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

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References

Emelia, J. B., Muntner, P., Alonso, A., Bittencourt, M. S., Callaway, C. S., Carson, A. P., Chamberlain, A. M., Chang, A. R., Cheng, S., Das, S. R., Delling, F. N., Djousse, L., Djousse, M. S. V., Ferguson, J. F., Fornage, M., Jordan, J. F., Khan, S. S., Kissela, B. M., Knutson, K. L., Kwan, T. W., Lackland, D. T., Lewis, T. T., Lichtman, J. H., Longenecker, C. T., Loop, M. S., Lutsey, P. T., Martin, S. S., Matsushita, K., Moran, A. E., Mussolino, M. E., O’Flaherty, M., Pandey, A., Perak, A. M., Rosamond, W. D., Roth, G. A., Sampson, U. K. A., Satou, G. M., Schroeder, E. B., Shah, S. H., Spartano, N. L., Stokes, A., Tirschwell, D. L., Tsao, C. W., Turakhia, M. P., VanWagner, L. B., Wilkins, J. T., Wong, S. S., Virani, S. S. and American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee, “Heart disease and stroke statistics-2019 update: A report from the American heart association,” Circulation 139(10), e56e528 (2019).Google Scholar
McDonald, M. W., Black, S. E., Copland, D. A., Corbett, D., Dijkhuizen, R. M., Farr, T. D., Jeffers, M. S., Kalaria, R. N., Karayanidis, F., Leff, A. P., Nithianantharajah, J., Pendlebury, S., Quinn, T. J., Clarkson, A. N. and O’Sullivan, M. J., “Cognition in stroke rehabilitation and recovery research: Consensus-based core recommendations from the second stroke recovery and rehabilitation roundtable,” Int J Stroke 14(8), 774782 (2019).CrossRefGoogle ScholarPubMed
Gittler, M. and Davis, A. M., “Guidelines for adult stroke rehabilitation and recovery,” JAMA 319(8), 820 (2018).CrossRefGoogle ScholarPubMed
Stinear, C. M., Lang, C. E., Zeiler, S. and Byblow, W. D., “Advances and challenges in stroke rehabilitation,” Lancet Neurol 19(4),348360 (2020).CrossRefGoogle ScholarPubMed
Huang, V. S. and Krakauer, J. W., “Robotic neurorehabilitation: A computational motor learning perspective,” J NeuroEng Rehabil 6(1), 5 (2009).CrossRefGoogle ScholarPubMed
Mehrholz, J., Pohl, M., Platz, T., Kugler, J. and Elsner, B., “Electromechanical and robot-assisted arm training for improving activities of daily living arm function, and arm muscle strength after stroke,” Cochrane Database of Syst Rev (2015). doi: 10.1002/14651858.cd006876.pub4.CrossRefGoogle ScholarPubMed
Laut, J., Porfiri, M. and Raghavan, P., “The present and future of robotic technology in rehabilitation,” Curr Phys Med Rehabil Rep 4(4), 312319 (2016).CrossRefGoogle ScholarPubMed
Gouttefarde, M., Lamaury, J., Reichert, C. and Bruckmann, T., “A versatile tension distribution algorithm for -DOF parallel robots driven by n+2 cables,” IEEE Trans Robot 31(6), 14441457 (2015).CrossRefGoogle Scholar
Liu, H., Gosselin, C. and Laliberté, T., “Conceptual design and static analysis of novel planar spring-loaded cable-loop-driven parallel mechanisms,” J Mech Robot 4(2), 021001 (2012).CrossRefGoogle Scholar
Zanotto, D., Rosati, G., Minto, S. and Rossi, A., “Sophia-3: A semiadaptive cable-driven rehabilitation device with a tilting working plane,” IEEE Trans Robot 30(4), 974979 (2014).CrossRefGoogle Scholar
Mengli, S., Yiming, O., Hu, J., Zhenyi, C., Changyang, W., Jiyu, L., Min, X., Weihua, L., Liu, W. and Shiwu, Z., “A soft-packaged and portable rehabilitation glove capable of closed-loop fine motor skills’,” Nat Mach Intell 5(10), 11491160 (2023).Google Scholar
Khadem, M., Inel, F., Carbone, G. and Slimane Tich Tich, A., “A novel pyramidal cable-driven robot for exercising and rehabilitation of writing tasks’,” Robotica 41(11), 34633484 (2023).CrossRefGoogle Scholar
Zhang, R., Xie, D., Qian, C., Duan, X. and Li, C., “Design of a flexible robot toward transbronchial lung biopsy’,” Robotica 41, 10551065 (2023).CrossRefGoogle Scholar
Rodriguez-Barroso, A., Khan, M., Santamaria, V., Sammarchi, E., Saltaren, R. and Agrawal, S., “Simulating underwater human motions on the ground with a cable-driven robotic platform,” IEEE Trans Robot 39(1), 783790 (2023).CrossRefGoogle Scholar
Izard, J.-B., Gouttefarde, M., Michelin, M., Tempier, O. and Baradat, C., “A Reconfigurable Robot for Cable-Driven Parallel Robotic Research and Industrial Scenario Proofing,” In: Mechanisms and Machine Science. Cable-Driven Parallel Robots, (Springer, 2013) pp. 135148.CrossRefGoogle Scholar
Sturm, C., Wildan, L. and Bruckm, T., “Wire robot suspension systems for wind tunnels,” Wind Tunnels Experim Fluid Dyn Res 2, 30–50 (2012).Google Scholar
MartinJ.-D. Otis, T.-L. N.-D., Laliberté, T., Ouellet, D., Laurendeau, D. and Gosselin, C., Cable tension control and analysis of reel transparency for 6-DOF haptic foot platform on a cable-driven locomotion interface. CERN european organization for nuclear research – zenodo, (2009).Google Scholar
Lenarčič, J. and Stanišić, M., Advances in Robot Kinematics: Motion in Man and Machine (Springer, 2010).CrossRefGoogle Scholar
Fattah, A. and Agrawal, S. K., “On the design of cable-suspended planar parallel robots,” J Mech Design 127(5), 10211028 (2005).CrossRefGoogle Scholar
Pusey, J., Fattah, A., Agrawal, S. and Messina, E., “Design and workspace analysis of a 6-6 cable-suspended parallel robot,” Mech Mach Theory 39(7), 761778 (2004).CrossRefGoogle Scholar
Kawamura, S., Choe, W., Tanaka, S. and Pandian, S. R., “Development of an Ultrahigh Speed Robot FALCON Using Wire Drive System,” In: Proceedings of 1995 IEEE International Conference on Robotics and Automation (2002) pp. 215–220.Google Scholar
Su, Y. X., Duan, B. Y., Nan, R. D. and Peng, B., “Development of a large parallel-cable manipulator for the feed-supporting system of a next-generation large radio telescope,” J Robotic Syst 18(11), 633643 (2001).CrossRefGoogle Scholar
Fang, S., Franitza, D., Torlo, M., Bekes, F. and Hiller, M., “Motion control of a tendon-based parallel manipulator using optimal tension distribution,” IEEE/ASME Trans Mechatron 9(3), 561568 (2004).CrossRefGoogle Scholar
Vallery, H., Lutz, J.von Z., Rauter, G., Fritschi, M., Everarts, C., Ronsse, R., Curt, A. and Bolliger, M., “Multidirectional Transparent Support for Overground Gait Training,” In: IEEE 13th International Conference on Rehabilitation Robotics (ICORR), (2013) pp. 1–7.Google Scholar
Jamshidifar, H., Khajepour, A., Fidan, B. and Rushton, M., “Kinematically-constrained redundant cable-driven parallel robots: Modeling, redundancy analysis, and stiffness optimization,” IEEE/ASME Trans Mechatron 22(2), 921930 (2017).CrossRefGoogle Scholar
Bruckmann, T., Mikelsons, L., Brandt, T., Hiller, M. and Schramm, D., “Wire Robots Part I: Kinematics, Analysis & Design,” In: Parallel Manipulators, New Developments (2012).Google Scholar
Renfrew, A., “Book review: Introduction to robotics: Mechanics and control,” Int J Electr Eng Educ 41(4), 388388 (2004).CrossRefGoogle Scholar
Macfarlane, S. and Croft, E. A., “Jerk-bounded manipulator trajectory planning: Design for real-time applications,” IEEE T Robotic Autom 19(1), 4252 (2003).CrossRefGoogle Scholar
Verhoeven, R., Analysis of the workspace of tendon-based stewart platforms advance access published July, (2004).Google Scholar
Kraus, W. and Pott, A., “Scenario-Based Dimensioning of the Actuator of Parallel Cable-Driven Robots,” In: New Trends in Mechanism and Machine Science, Mechanisms and Machine Science, (Springer, 2013) pp. 131139.CrossRefGoogle Scholar
Verhoeven, R., Hiller, M. and Tadokoro, S., “workspace, Singularities and Classification of Tendon-Driven Stewart Platforms,” In: Advances in Robot Kinematics: Analysis and Control, (1998) pp. 105114.CrossRefGoogle Scholar
Cui, Z. and Tang, X., “Analysis of stiffness controllability of a redundant cable-driven parallel robot based on its configuration,” Mechatronics 75, 102519 (2021).CrossRefGoogle Scholar
Ferravante, V., Riva, E., Taghavi, M., Braghin, F. and Bock, T., “Dynamic analysis of high precision construction cable-driven parallel robots,” Mech Mach Theory 135, 5464 (2019).CrossRefGoogle Scholar
Mikelsons, L., Bruckmann, T., Hiller, M. and Schramm, D., “A Real-Time Capable Force Calculation Algorithm for Redundant Tendon-Based Parallel Manipulators,” In: 2008 IEEE International Conference on Robotics and Automation, (2008).CrossRefGoogle Scholar
Lim, W. B., Yeo, S. H. and Yang, G., “Optimization of tension distribution for cable-driven manipulators using tension-level index,” IEEE/ASME Trans Mechatron 19(2), 676683 (2014).CrossRefGoogle Scholar
Gouttefarde, M., Lamaury, J., Reichert, C. and Bruckmann, T., “A versatile tension distribution algorithm for n-DOF parallel robots driven by n+2 cables,” IEEE Trans Robot 31(6),14441457 (2015).CrossRefGoogle Scholar
Wang, Y.-L., Wang, K.-Y., Chai, Y.-J., Mo, Z.-J. and Wang, K.-C., “Research on mechanical optimization methods of cable-driven lower limb rehabilitation robot,” Robotica 40(1), 154169 (2022). doi: 10.1017/S0263574721000448.CrossRefGoogle Scholar