Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-19T11:51:40.272Z Has data issue: false hasContentIssue false

Design-to-Workspace Synthesis of a Cable Robot Used in Legs Training Machine

Published online by Cambridge University Press:  22 November 2019

Houssein Lamine*
Affiliation:
Mechanical Laboratory of Sousse (LMS), National Engineering School of Sousse, University of Sousse, Sousse 4000, Tunisia
Lotfi Romdhane
Affiliation:
Mechanical Engineering Department, American University of Sharjah, PO Box 26666, Sharjah, United Arab Emirates
Houssem Saafi
Affiliation:
Preparatory Institute for Engineering Studies of Gafsa, University of Gafsa, Gafsa 2000, Tunisia
Sami Bennour
Affiliation:
Mechanical Laboratory of Sousse (LMS), National Engineering School of Sousse, University of Sousse, Sousse 4000, Tunisia
*
*Corresponding author. E-mail: houssein.lamine@gmail.com

Summary

This paper deals with a continuous design task of a planar cable robot used in a gait training machine called the cable-driven legs trainer. The design of cable robots requires satisfying two constraints, that is, tensions in the cables must remain non-negative, and cable interferences should be avoided. The carried design approach is based on interval analysis, which is one of the most efficient methods to obtain certified results. The constraints of non-negative tensions and cable to end-effector interference are solved using interval analysis tools. By means of a dynamic simulation, the reached workspace and the produced wrenches of the cable robot are evaluated as a set of interval vectors. An optimization algorithm is then designed to optimize the cable robot structure for the gait training machine. The robot is designed to produce non-negative tensions in the cables and to avoid collision at all times within the desired workspace and under the required external loads.

Type
Articles
Copyright
© Cambridge University Press 2019

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

Tang, X., “An overview of the development for cable-driven parallel manipulator,” Adv. Mech. Eng. 6, 823028 (2014).CrossRefGoogle Scholar
Nguyen, D. Q., Gouttefarde, M., Company, O. and Pierrot, F., “On the Analysis of Large-Dimension Reconfigurable Suspended Cable-Driven Parallel Robots,” 2014 IEEE International Conference on Robotics and Automation (ICRA) (2014) pp. 57285735.Google Scholar
Wu, M. and Landry, J. M., “Lower Extremity Flexible Assist Devices for Locomotion,” In: Neurorehabilitation Technology (Dietz, V., Nef, T. and Rymer, W. Z., eds.) (Springer, London, 2012) pp. 361378.Google Scholar
Bosscher, P., Riechel, A. T. and Ebert-Uphoff, I., “Wrench-feasible workspace generation for cable-driven robots,” IEEE Trans. Robot. 22(5), 890902 (2006).CrossRefGoogle Scholar
Duan, Q. J. and Duan, X., “Workspace classification and quantification calculations of cable-driven parallel robots,” Adv. Mech. Eng. 6, 358727 (2014).CrossRefGoogle Scholar
Lamine, H., Bennour, S. and Romdhane, L., “Design of cable-driven parallel manipulators for a specific workspace using interval analysis,” Adv. Robot. 30(9), 585594 (2016).CrossRefGoogle Scholar
Gagliardini, L., Caro, S., Gouttefarde, M., Wenger, P. and Girin, A., “Optimal Design of Cable-Driven Parallel Robots for Large Industrial Structures,2014 IEEE International Conference on Robotics and Automation (ICRA), Hong Kong (2014) pp. 57445749.Google Scholar
Nguyen, D. Q. and Gouttefarde, M., “On the improvement of cable collision detection algorithms,” In: Cable-Driven Parallel Robots (Pott, A. and Bruckmann, T., eds.) (Springer, Cham, 2015) pp. 2940.Google Scholar
Williams, R. L. and Gallina, P., “Planar cable-direct-driven robots: Design for wrench exertion,” J. Intell. Robot. Syst. 35(2), 203219 (2002).CrossRefGoogle Scholar
Aref, M. M. and Taghirad, H. D., “Geometrical Workspace Analysis of a Cable-Driven Redundant Parallel Manipulator: KNTU CDRPM,” IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2008, Nice, France (2008) pp. 1958–1963.Google Scholar
Blanchet, L. and Merlet, J., “Interference Detection for Cable-Driven Parallel Robots (CDPRs),” In: 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Besacon (2014) pp. 14131418.Google Scholar
Fiedler, M., Nedoma, J., Ramik, J., Rohn, J. and Zimmermann, K., Linear Optimization Problems with Inexact Data (Springer, Boston, USA, 2006).Google Scholar
Lamine, H., Amine Laribi, M., Bennour, S., Romdhane, L. and Zeghloul, S., “Design study of a cable-based gait training machine,” J. Bionic Eng. 14(2), 232244 (2017).CrossRefGoogle Scholar
Merlet, J.-P. and Daney, D., “Legs Interference Checking of Parallel Robots Over a Given Workspace or Trajectory,” Proceedings 2006 IEEE International Conference on Robotics and Automation, ICRA 2006, Orlando, FL, USA (2006) pp. 757762.Google Scholar
FarzanehKaloorazi, M., Masouleh, M. T. and Caro, S., “Collision-free workspace of parallel mechanisms based on an interval analysis approach,” Robotica 35(8), 17471760 (2016).CrossRefGoogle Scholar
Benito-Penalva, J., Edwards, D., Opisso, E., Cortes, M., Lopez-Blazquez, R., Murillo, N., Costa, U., Tormos, J., Vidal-Samsó, J., Valls-Solé, J. and Medina, J., “Gait training in human spinal cord injury using electromechanical systems: Effect of device type and patient characteristics,” Arch. Phys. Med. Rehabil. 93(3), 404412 (2012).CrossRefGoogle ScholarPubMed
Dutra, C. M. R., Dutra, C. M. R., Moser, A. D. de L. and Manffra, E. F., “Locomotor training with partial body weight support in spinal cord injury rehabilitation: Literature review,” Fisioter. em Mov. 26(4), 907920 (2013).CrossRefGoogle Scholar
Hussain, S., Xie, S. Q. and Liu, G., “Robot assisted treadmill training: Mechanisms and training strategies,” Med. Eng. Phys. 33(5), 527533 (2011).CrossRefGoogle ScholarPubMed
Pham, C. B., Yeo, S. H., Yang, G. and Chen, I.-M., “Workspace analysis of fully restrained cable-driven manipulators,” Rob. Auton. Syst. 57(9), 901912 (2009).CrossRefGoogle Scholar
Gouttefarde, M., Daney, D. and Merlet, J.-P., “Interval-analysis-based determination of the wrench-feasible workspace of parallel cable-driven robots,” IEEE Trans. Robot. 27(1), 113 (2011).CrossRefGoogle Scholar
Jaulin, L., Applied Interval Analysis: With Examples in Parameter and State Estimation, Robust Control and Robotics, vol. 1 (Springer, Science & Business Media, London, 2001).CrossRefGoogle Scholar
Lamine, H., Bennour, S. and Romdhane, L., “Dynamic Simulation of a Cable-Based Gait Training Machine,” In: Robotics and Mechatronics, vol. 37 (S. Zeghloul, M. Laribi and J. P. Gazeau, eds.) (Springer, Cham, 2016) pp. 199207.CrossRefGoogle Scholar
Winter, D. A., Biomechanics and Motor Control of Human Movement (John Wiley & Sons, Hoboken, NJ, USA, 2009).CrossRefGoogle Scholar
Hocoma, AG, “Lokomat – Hocoma.” [Online]. Available: https://www.hocoma.com/world/en/products/lokomat/. [Accessed: 20-Oct-2019].Google Scholar
Rump, S., “INTLAB — INTerval LABoratory,” In: Developments in Reliable Computing SE – 7 (Csendes, T., ed.), (Springer, Dordrecht, Netherlands, 1999) pp. 77104.Google Scholar
Gagliardini, L., Caro, S., Gouttefarde, M. and Girin, A., “Discrete reconfiguration planning for cable-driven parallel robots,” Mech. Mach. Theory 100, 313337 (2016).CrossRefGoogle Scholar