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A reconfigurable, tendon-based haptic interface for research into human-environment interactions

Published online by Cambridge University Press:  14 August 2012

Joachim von Zitzewitz ,
André Morger ,
Georg Rauter ,
Laura Marchal-Crespo ,
Francesco Crivelli ,
Dario Wyss ,
Tobias Bruckmann  and
Robert Riener
Joachim von Zitzewitz*
Affiliation:
Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), ETH Zurich, 8092 Zurich, Switzerland Brain Mind Institute, EPFL Lausanne, 1015 Lausanne, Switzerland
André Morger
Affiliation:
Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), ETH Zurich, 8092 Zurich, Switzerland
Georg Rauter
Affiliation:
Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), ETH Zurich, 8092 Zurich, Switzerland
Laura Marchal-Crespo
Affiliation:
Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), ETH Zurich, 8092 Zurich, Switzerland
Francesco Crivelli
Affiliation:
Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), ETH Zurich, 8092 Zurich, Switzerland
Dario Wyss
Affiliation:
Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), ETH Zurich, 8092 Zurich, Switzerland
Tobias Bruckmann
Affiliation:
Chair for Mechatronics, University Duisburg-Essen, 47057 Duisburg, Germany
Robert Riener
Affiliation:
Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), ETH Zurich, 8092 Zurich, Switzerland Medical Faculty, University of Zurich, 8092 Zurich, Switzerland
*
*Corresponding author. E-mail: [email protected]
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Summary

Human reaction to external stimuli can be investigated in a comprehensive way by using a versatile virtual-reality setup involving multiple display technologies. It is apparent that versatility remains a main challenge when human reactions are examined through the use of haptic interfaces as the interfaces must be able to cope with the entire range of diverse movements and forces/torques a human subject produces. To address the versatility challenge, we have developed a large-scale reconfigurable tendon-based haptic interface which can be adapted to a large variety of task dynamics and is integrated into a Cave Automatic Virtual Environment (CAVE). To prove the versatility of the haptic interface, two tasks, incorporating once the force and once the velocity extrema of a human subject's extremities, were implemented: a simulator with 3-DOF highly dynamic force feedback and a 3-DOF setup optimized to perform dynamic movements. In addition, a 6-DOF platform capable of lifting a human subject off the ground was realized. For these three applications, a position controller was implemented, adapted to each task, and tested. In the controller tests with highly different, task-specific trajectories, the three robot configurations fulfilled the demands on the application-specific accuracy which illustrates and confirms the versatility of the developed haptic interface.

Keywords

Haptic interfacesParallel manipulatorsDesignMan–machine systemsControl of robotic systems
Type
Articles
Information
Robotica , Volume 31 , Issue 3 , May 2013 , pp. 441 - 453
Copyright
Copyright © Cambridge University Press 2012

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References

1.Ham, R., Sugar, T., Vanderborght, B., Hollander, K. and Lefeber, D., “Compliant actuator designs,” IEEE Robot. Autom. Mag. 16 (3), 81–94 (Sept. 2009).CrossRefGoogle Scholar
2.Vallery, H., Veneman, J., van Asseldonk, E., Ekkelenkamp, R., Buss, M. and van Der Kooij, H., “Compliant actuation of rehabilitation robots,” IEEE Robot. Autom. Mag. 15 (3), 60–69 (Sept. 2008).CrossRefGoogle Scholar
3.Marchal-Crespo, L. and Reinkensmeyer, D., “Review of control strategies for robotic movement training after neurologic injury,” J. NeuroEngineering and Rehabil. 6 (1), 20 (2009).CrossRefGoogle ScholarPubMed
4.Riener, R., Duschau-Wicke, A., König, A., Bolliger, M., Wieser, M. and Vallery, H., “Automation in Rehabilitation: How to Include the Human into the Loop,” World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, volume 25/13 of IFMBE Proceedings (Magjarevic, R., Dössel, O. and Schlegel, W. C., eds.), (Springer Berlin Heidelberg, 2009) pp. 180–183.CrossRefGoogle Scholar
5.Koenig, A., Novak, D., Omlin, X., Pulfer, M., Perreault, E., Zimmerli, L., Mihelj, M. and Riener, R., “Real-time closed-loop control of cognitive load in neurological patients during robot-assisted gait training,” IEEE Trans. Neural Syst. Rehabil. Eng. 19 (4), 453–464 (Aug. 2011).CrossRefGoogle ScholarPubMed
6.Andreassi, J. L., Psychophysiology: Human Behavior and Physiological Response (Lawrence Erlbaum Assoc Inc, 2006).Google Scholar
7.Welch, C. M., Banks, S. A., Cook, F. F. and Draovitch, P., “Hitting a baseball: A biomechanical description,” J. Orthopaedic and Sports Physical Therapy 22, 193–193 (1995).CrossRefGoogle ScholarPubMed
8.Bahamonde, R. E. and Knudson, D., “Kinetics of the upper extremity in the open and square stance tennis forehand,” J. Sci. Med. Sport. 6 (1), 88–101 (2003).CrossRefGoogle ScholarPubMed
9.Plagenhoef, S., Patterns of Human Motion: A Cinematographic Analysis (Prentice-Hall Englewood Cliffs, NJ, 1971).Google Scholar
10.Steinacker, J. M., Lormes, W., Lehmann, M. and Altenburg, D., “Training of rowers before world championships,” Med. Sci. Sports & Exercise. 30 (7), 1158 (1998).CrossRefGoogle ScholarPubMed
11.Cabrera, D., Ruina, A. and Kleshnev, V., “A simple 1+ dimensional model of rowing mimics observed forces and motions,” Hum. Mov. Sci. 25 (2), 192–220 (2006).CrossRefGoogle ScholarPubMed
12.Massie, T. H. and Salisbury, J. K., “The Phantom Haptic Interface: A Device for Probing Virtual Objects,” Proceedings of the ASME Winter Annual Meeting, Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, Chicago, IL (Nov. 1994) vol. 1, pp. 316–317.Google Scholar
13.Grange, S., Conti, F., Rouiller, P., Helmer, P. and Baur, C., “The delta haptic device,” Mecatronics 2001 (2001).Google Scholar
14.Colgate, E. and Hogan, N., “An Analysis of Contact Instability in Terms of Passive Physical Equivalents,” Proceedings of the IEEE International Conference on Robotics and Automation, IEEE, Scottsdale, AZ (May 1989) pp. 404–409.Google Scholar
15.Wellner, M., Sigrist, R. and Riener, R., “Virtual competitors influence rowers,” PRESENCE: Teleoperators and Virtual Environments. 19 (4), 313–330 (2010).CrossRefGoogle Scholar
16.Lawrence, D. A., Pao, L.Y., White, A. C. and Xu, W., “Low Cost Actuator and Sensor for High-Fidelity Haptic Interfaces,” Proceedings of the 12th International Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, Chicago, IL (March 2004) pp. 74–81.Google Scholar
17.Astley, O. R. and Hayward, V., “Design Constraints for Haptic Surgery Simulation,” IEEE International Conference on Robotics and Automation, 2000. Proceedings. ICRA'00, San Francisco, CA (Apr. 2000) vol. 3, pp. 2446–2451.Google Scholar
18.Lawrence, D. A., Pao, L. Y. and Aphanuphong, S., “Bow Spring/Tendon Actuation for Low Cost Haptic Interfaces,” First Joint Eurohaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, Pisa, Italy (March 2005) pp. 157–166.CrossRefGoogle Scholar
19.Riener, R., Lünenburger, L., Maier, I. C., Colombo, G. and Dietz, V., “Locomotor training in subjects with sensory-motor deficits: An overview of the robotic gait orthosis lokomat,” J. Healthc. Eng. 1 (2), 197–216 (2010).CrossRefGoogle Scholar
20.Wilson, R. and Niemeyer, G., “Motion Control of Impedance-Type Haptic Devices,” Proceedings of the IEEE International Conference on Robotics and Automation, ICRA '09. Kobe, Japan (May 2009) pp. 1092–1097.Google Scholar
21.Merlet, J.-P. and Daney, D., “A New Design for Wire-Driven Parallel Robot,” Proceedings of the Design and Modelling of Mechanical Systems, 2nd World Congress, Monastir, Tunisia (March 2007).Google Scholar
22.von Zitzewitz, J., Rauter, G., Steiner, R., Brunschweiler, A. and Riener, R., “A Versatile Wire Robot Concept as a Haptic Interface for Sport Simulation,” In: Proceedings of the 2009 IEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan (12–17 May 2009) pp. 313–318.CrossRefGoogle Scholar
23.Merlet, J.-P., “Marionet, a Family of Modular Wire-Driven Parallel Robots,” In: Advances in Robot Kinematics: Motion in Man and Machine (Lenarcic, J. and Stanisic, M. M., eds.) (Springer Netherlands, 2010) pp. 53–61.CrossRefGoogle Scholar
24.von Zitzewitz, J., Rauter, G., Vallery, H., Morger, A. and Riener, R., “Forward Kinematics of Redundantly Actuated, Tendon-Based Robots,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS '10, Taipei, Taiwan (Oct. 2010) pp. 2289–2294.Google Scholar
25.Bouri, M., Le Gall, B. and Clavel, R., “A New Concept of Parallel Robot for Rehabilitation and Fitness: The Lambda,” Proceedings of the IEEE International Conference on Robotics and Biomimetics (ROBIO), Guilin, China (Dec. 2009) pp. 2503–2508.Google Scholar
26.Mayhew, D., Bachrach, B., Rymer, W. Z. and Beer, R. F., “Development of the MACARM - A Novel Cable Robot for Upper Limb Neurorehabilitation,” Proceedings of the 9th International Conference on Rehabilitation Robotics, ICORR, Chicago, IL (June/July 2005) pp. 299–302.Google Scholar
27.EtherCAT Technology Group, “Ethercat - the ethernet fieldbus. http://www.ethercat.org/en/technology.html (March 2011).Google Scholar
28.von Zitzewitz, J., Wolf, P., Novakovic, V., Wellner, M., Rauter, G., Brunschweiler, A. and Riener, R., “A real-time rowing simulator with multi-modal feedback,” Sports Technol. 1 (6), 257–266 (2009).CrossRefGoogle Scholar
29.Rauter, G., Sigrist, R., Marchal-Crespo, L., Vallery, H., Riener, R. and Wolf, P., “Assistance or Challenge? Filling a Gap in User-Cooperative Control,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2011, San Francisco, CA (Sep. 2011).Google Scholar
30.Carignan, C. R. and Cleary, K. R., “Closed-loop force control for haptic simulation of virtual environments,” Haptics-e. 1 (2), 1–14 (2000).Google Scholar
31.Jezernik, S., Colombo, G., Keller, T., Frueh, H. and Morari, M., “Robotic orthosis lokomat: A rehabilitation and research tool,” Neuromodulation. 6 (2), 108–115 (2003).CrossRefGoogle ScholarPubMed
32.Fang, S., Design, Modeling and Motion Control of Tendon-Based Parallel Manipulators (VDI Fortschritt-Bericht, 2005).Google Scholar
33.Ferreau, H. J., Ortner, P., Langthaler, P., del Re, L. and Diehl, M., “Predictive control of a real-world diesel engine using an extended online active set strategy,” Annu. Rev. Control. 31 (2), 293–301 (2007).CrossRefGoogle Scholar
34.Verhoeven, R., Analysis of the Workspace of Tendon-Based Stewart Platforms Ph.D. thesis (Duett, Universitätsbibliothek Duisburg, 2004).Google Scholar
35.Rauter, G., von Zitzewitz, J., Duschau-Wicke, A., Vallery, H. and Riener, R., “A Tendon-Based Parallel Robot Applied to Motor Learning in Sports,” Proceedings of the 3rd IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2010, Tokio, Japan (Sep. 2010) pp. 82–87.Google Scholar
36.Reding, G. R. and Fernandez, C., “Effects of vestibular stimulation during sleep,” Electroencephalogr. Clin. Neurophysiol. 24 (1), 75–79 (1968).CrossRefGoogle ScholarPubMed
37.Jones, G. M. and Sugie, N, “Vestibulo-ocular responses in man during sleep,” Electroencephalogr. Clin. Neurophysiol. 32 (1), 43 (1972).CrossRefGoogle ScholarPubMed
38.Tauber, E. S., Handelman, G., Handelman, R. and Weitzman, E. D., “Vestibular stimulation during sleep in young adults,” Arch. Neurol. 27 (3), 221–228 (Sep 1972).CrossRefGoogle ScholarPubMed
39.Ornitz, E. M., Forsythe, A. B. and De la Pea, A., “The effect of vestibular and auditory stimulation on the rapid eye movements of rem sleep in normal children,” Electroencephalogr. Clin. Neurophysiol. 34 (4), 379–390 (Apr 1973).CrossRefGoogle ScholarPubMed
40.Woodward, S., Tauber, E. S., Spielmann, A. J. and Thorpy, M. J., “Effects of otolithic vestibular stimulation on sleep,” Sleep. 13 (6), 533–537 (Dec. 1990).CrossRefGoogle ScholarPubMed
41.Constantinescu, I., Bayer, L., Perrig, S., Vidal, P., Muhlethaler, M. and Schwartz, S., “Rock to sleep: The impact of gentle rocking on an afternoon nap,” Eurpean Sleep Res. Soc., Lisbon, Portugal (Sep. 2010).Google Scholar
42.Moore, K. L., Iterative Learning Control for Deterministic Systems (Springer-Verlag New York, Inc. Secaucus, NJ, USA, 1993).CrossRefGoogle Scholar
43.Duschau-Wicke, A., von Zitzewitz, J., Banz, R. and Riener, R., “Iterative Learning Synchronization of Robotic Rehabilitation Tasks,” Proceedings of the IEEE 10th International Conference on Rehabilitation Robotics, ICORR 2007, IEEE, Noordwijk, the Netherlands (June 2007) pp. 335–340.CrossRefGoogle Scholar
44.Kawamura, S., Ida, M. and Wada, T., “Development of a Virtual Sports Machine using a Wire Drive System - A Trial of Virtual Tennis,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Pittsburgh (1995) pp. 111–116.Google Scholar
45.Omlin, X., von Zitzewitz, J., Rauter, G., Morger, A. and Riener, R., “Robot-Driven Platform to Investigate Effects of Vestibular Stimulation on Sleep,” Proceedings of the 19th Annual Meeting of the German Society for Sleep Research and Sleep Medicine, Mannheim, Germany (November 2011).Google Scholar