Advertisement

Autonomous Robots

, Volume 16, Issue 2, pp 165–191 | Cite as

Integration of a Rehabilitation Robotic System (KARES II) with Human-Friendly Man-Machine Interaction Units

  • Zeungnam Bien
  • Myung-Jin Chung
  • Pyung-Hun Chang
  • Dong-Soo Kwon
  • Dae-Jin Kim
  • Jeong-Su Han
  • Jae-Hean Kim
  • Do-Hyung Kim
  • Hyung-Soon Park
  • Sang-Hoon Kang
  • Kyoobin Lee
  • Soo-Chul Lim
Article

Abstract

In this paper, we report some important results of design and evaluation of a wheelchair-based robotic arm system, named as KARES II (KAIST Rehabilitation Engineering Service System II), which is newly developed for the disabled. KARES II is designed in consideration of surveyed necessary tasks for the target users (that is, people with spinal cord injury). At first, we predefined twelve important tasks according to extensive interviews and questionnaires. Next, based on these tasks, all subsystems are designed, simulated and developed. A robotic arm with active compliance and intelligent visual servoing capability is developed by using cable-driven mechanism. Various kinds of human-robot interfaces are developed to provide broad range of services according to the levels of disability. Eye-mouse, shoulder/head interface, EMG signal-based control subsystems are used for this purpose. Besides, we describe the process of integration of our rehabilitation robotic system KARES II, and discuss about user trials. A mobile platform and a wheelchair platform are two main platforms in which various subsystems are installed. For a real-world application of KARES II system, we have performed user trials with six selected potential end-users (with spinal cord injury).

service robot rehabilitation robot wheelchair-based robotic arm human-robot interaction task specific cable-driven mechanism intelligent visual servoing Eye-mouse bio-signal (EMG) based control head/shoulder interface user trials task-oriented design 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Afma-robots, AFMASTER, http://www.afma-robots.com.Google Scholar
  2. Applied Science Laboratories, Model 504. http://www.a-s-l.com/ 504 home.htmGoogle Scholar
  3. Applied Science Laboratories, Model 501. http://www.a-s-l.com/ 501 home.htmGoogle Scholar
  4. Basmajian, J.V. and De Luca, C.J. 1985. Muscle Alive, Williams & Wilkins, 5th edition.Google Scholar
  5. Bien, Z. and Song, W.-K. 2000. Novel wheelchair-based robotic arm with visual servoing capability for human-robot interaction. In Workshop on Service Automation and Robotics, Hong Kong, June, pp. 5-17.Google Scholar
  6. Bolduc, M. and Levine, M.D. 1998. A review of biologically motivated space-variant data reduction models for robotic vision. Computer Vision and Image Understanding, 69(2):170-184.Google Scholar
  7. Chang, P.-H. and Park, H.-S. 2003. Development of a robotic arm for handicapped people: A task-oriented design approach.Will be appeared in Autonomous Robots, vol. 15.Google Scholar
  8. Chang, P.-H. et al. 2003. Active compliance control for the disabled with cable transmission. In Proceedings of ICORR2003, pp. 84-87.Google Scholar
  9. Choi, J. 2001. Design of a behavior-based controller using a novel camera head and its application to service robots. MS Thesis, KAIST, Korea. (in Korean)Google Scholar
  10. Chen, N. and Parker, G.A. 1994. Inverse kinematic solution to a calibrated puma 560 industrial robot. Control Engineering Practice, 2:239-245.Google Scholar
  11. Colello, M.S. and Mahoney, R.M. 2002. Commercializing assistive and therapy robotics. In Universal Access and Assistive Technogy, S. Keates et al. (Eds.), pp. 223-234.Google Scholar
  12. Conte, G., Longhi, S., and Zulli, R. 1996. Motion planning for unicycle and car-like robots. International Journal of Systems Science, 27(8):791-798.Google Scholar
  13. Craig, J.J. 1989. Introduction to Robotics: Mechanics and Control, Addison-Wesley Publishing Co.Google Scholar
  14. Dallaway, J.L., Jackson, R.D., and Timmers, P.H.A. 1995. Rehabilitation robotics in Europe. IEEE Tr. on Rehabilitation Engineering, 3:35-45.Google Scholar
  15. Ebisawa, Y. 1998. Improved video-based eye-gaze detection method. IEEE Trans. on Instrument and Measurement, 47(4):948-955.Google Scholar
  16. Eftring, H. and Boschian, K. 1999. Technical results from MANUS user trials. In Proc. 6th Int. Conf. on Rehabilitation Robotics, pp. 136-141.Google Scholar
  17. Erlandson, R.F. 1995. Applications of robotic/mechatronic systems in special education, rehabilitation therapy, and vocational training: A paradigm shift. IEEE Tr. on Rehabilitation Engineering, 3:22-32.Google Scholar
  18. FSR an Overview of the technology. Tech-Storm Co., Ltd.Google Scholar
  19. Glenstrup, A.J. and Engell-Nielsen, T. 1995. Eye controlled media: Present and future state. B.S. Dissertation, Copenhagen University.Google Scholar
  20. Gomi, H. and Kawato, M. 1997. Human arm stiffness and equilibrium-point trajectory during multi-joint movement. Biological Cybernetics, 76:163-171.Google Scholar
  21. Han, J.-S., Bang, W.-C., and Bien, Z.Z. 2002. Feature set extraction algorithm based on soft computing techniques and its application to EMG pattern classification. Journal of Fuzzy Optimization and Decision Making, 1:269-286.Google Scholar
  22. Harwin, W.S., Rahman, T., and Foulds, R.A. 1995.Areview of design issues in rehabilitation robotics with reference to north American research. IEEE Tr. on Rehabilitation Engineering, 3:3-13.Google Scholar
  23. Hillman, M. 1998. Introduction to the special issue on rehabilitation robotics. Robotica, 16:485.Google Scholar
  24. Hillman, M., Hagan, K., Hagan, S., Jepson, J., and Orpwood, R. 2001. Integration of a robotic device onto a powered wheelchair. In 7th Int'l Conf. on Rehabilitation Robotics, Evry, France, pp. 192-198.Google Scholar
  25. Hillman, M.R. and Jepson, J. 1992. Evaluation of a robotic workstation for the disabled. J. of Biomedical Eng., 14:187-192.Google Scholar
  26. Hillman, M.R., Pullin, G.M., Gammie, A.R., Stammers, C.W., and Orpwood, R.D. 1990. Development of a robot arm andworkstation for the disabled. J. of Biomedical Eng., 12:199-204.Google Scholar
  27. Hillman, M.R., Pullin, G.M., Gammie, A.R., Stammers, C.W., and Orpwood, R.D. 1991. Clinical experience in rehabilitation robotics. J. of Biomedical Eng., 13:239-243.Google Scholar
  28. Hillman, M. et al. 2002. The weston wheelchair mounted assistive robot-The design story. Robotica, 20:125-132.Google Scholar
  29. Hogan, N. 1984. An organizing principle for a class of voluntary movements. Journal of Neuroscience, 4(11).Google Scholar
  30. Hsia, T.C. and Gao, L.S. 1990. Robot manipulator control using decentralized linear time-invariant time-delayed joint controllers. In IEEE Int. Conf. on Robotics and Automation, pp. 2070-2075.Google Scholar
  31. http://www.kscic.or.kr/relifeinfo/about/aboutsci.html#spineGoogle Scholar
  32. http://www.care-o-bot.de/english/Care-O-bot 2.phpGoogle Scholar
  33. http://www.shodor.org/interactivate/activities/boxplot/, 2002.Google Scholar
  34. http://www.bcdi.be/new/en/projects/data.htmlGoogle Scholar
  35. ISRA, 1995. The service robot market, an in-depth study from the international service association. ISRA, 1995.Google Scholar
  36. Iwata, H. et al. 1999. A physical interference adapting hardware system using MIA arm and humanoid surface covers. In Proc. of IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 1216-1221.Google Scholar
  37. Jain, R., Kasturi, R., and Schunck, B.G. 1995. Machine Vision, McGraw-Hill Book Co.Google Scholar
  38. Jebsen, R.H., Taylor, N., Trieschmann, R.B., Trotter, M.J., and Howard, L.A. 1969. An objective and standardized test of hand function. Arch. Phys. Med. Rehab., 50:311-319.Google Scholar
  39. Johnson, D.E. 1975. Rapid Practical Designs of Active filters, John Wiley & Sons.Google Scholar
  40. Jones, D.K., Cooper, R.A., Albright, S., and DiGiovine, M. 1998. Powered wheelchair driving performance using force-and position-sensing joysticks. In Proceedings of the IEEE 24th Annual Northeast Bioengineering Conference, April, pp. 130-132.Google Scholar
  41. Jruger,V. 1995. Optical flowcomputation in the complex logarithmic plane. Diploma-Thesis, University of Kiel, Germany.Google Scholar
  42. Kawamura, K. and Isakarous, M. 1994. Trends in service robots for the disabled and the elderly. In Proc. of IROS'94, pp. 1647-1654.Google Scholar
  43. Kim, J.-H., Lee, B.-R., Kim, D.-H. and Chung, M.-J. 2003. Eyemouse system for people with motor disabilities. In Proc. Int'l. Conf. Rehabilitation Robotics, pp. 159-163.Google Scholar
  44. Kim, D.-J., Song, W.-K., Han, J.-S., and Bien, Z.Z. 2002. Soft computing based intention reading techniques as a means of human-robot interaction for human centered system. Journal of Soft Computing, 7:160-166.Google Scholar
  45. Krebs, H.I., Hogan, N., Volpe, B.T., Aisen, M.L., Edelstein, L., and Diels, C. 1999. Robot-aided neuro-rehabilitation in stroke: Threeyear follow-up. In Proceedings of ICORR1999, pp. 34-41.Google Scholar
  46. Kwee, H.H. 1998. Integrated control of MANUS manipulator and wheelchair enhanced by environmental docking. Robotica, 16(5):491-498.Google Scholar
  47. Lee, B.-R. 2002.Areal-time eye-gaze tracking system using infrared rays and vision sensor. M.S. Dissertation, Korea Advanced Institute of Science and Technology.Google Scholar
  48. Lee, K. and Kwon, D.-S. 2000. Sensors and actuators of wearable haptic master device for the disabled. In Proceedings of the 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems( IROS), pp. 371-376.Google Scholar
  49. Lee, K. and Kwon, D.-S. 2001a. Wearable master device for spinal injured persons as a control device of motorized wheelchairs. Journal of Artificial Life and Robot, 4(4):182-187.Google Scholar
  50. Lee, K. andKwon, D.-S. 2001b.Wearable master device using optical fiber curvature sensors for the disabled. Proceedings 2001 ICRA, 1:892-896.Google Scholar
  51. Lum, P.S., Burgar, C.G., Shor, P.C., Majmundar, M., Van der Loos, H.F.M. 2002. Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper limb motor function after stroke. Arch. Phys. Med. Rehab., 83:952-959.Google Scholar
  52. Machiel Van der Loos, H.F. 1995.Va/Stanford rehabilitation robotics research and development program: Lessons learned in the application of robotics technology to the field of rehabilitation. IEEE Tr. on Rehabilitation Engineering, 3:46-55.Google Scholar
  53. Martens, C., Ivlev, O., Graser, A., Lang, O., and Ruchel, N. 2001. A friend for assisting handicapped people. IEEE Robotics and Automation Magazine, March 2001.Google Scholar
  54. Martens, C., Ivlev, O., and Graser, A. 2001. Interactive controlled robotic system FRIEND to assist disabled people. In 7th Int'l Conf. on Rehabilitation Robotics, Evry, France, pp. 148-154.Google Scholar
  55. Martens, C., Kim, D.-J., Han, J.-S., Graeser, A., and Bien, Z. 2002. Concept for a modified hybrid multi-layer control architecture for rehabilitation robots. In 3rd Int'l Workshop on HumanfriendlyWelfare Robotic Systems, pp. 49-54, Daejeon, Korea, Jan. 20-22.Google Scholar
  56. Netter, F.H. 1999. Atlas of Human Anatomy. NOVARTIS, 2nd edition.Google Scholar
  57. Peters II, R.A., Bishay, M., Cambron, M.E., and Negishi, K. 1996. Visual servoing for service robot. Robotics and Autonomous Systems, 18:213-224.Google Scholar
  58. Rao, R., Agrawal, S.K., and Scholz, J.P. 2000. A robot test-bed for assistance and assessment in physical therapy. Advanced Robotics, 14(7):565-578.Google Scholar
  59. Salisbury, J.K. Active stiffness control of manipulator in cartesian coordinates. In Proc. of 19th IEEE Conf. on Decision and Control, pp. 95-100.Google Scholar
  60. SensoMotoric Instrument, 3D VOG Video-oculography. [Online]. Available: http://www.smi.de/3d/index.htm Song, W.-K. 2003. Blend of soft computing techniques for effective human-machine interaction in service robotic systems. Fuzzy Sets and Systems, 134:5-25.Google Scholar
  61. Song, W.-K., Lee, H., and Bien, Z. 1999. KARES: Intelligent wheelchair-mounted robotic arm system using vision and force sensor. Robotics and Autonomous Systems, 28(1): 83-94.Google Scholar
  62. Tejima, N. 1996. Evaluation of rehabilitation robots for eating. In IEEE International Workshop on Robot and Human Communication, pp. 118-120.Google Scholar
  63. Topping, M. 2001. Handy 1, a robotic aid to independence for severely disabled people. In 7th Int'l Conf. on Rehabilitation Robotics, Evry, France, pp. 142-147.Google Scholar
  64. Townsend, W.T. 1988. The effect of transmission design on forcecontrolled manipulator performance. PhD Thesis, MIT.Google Scholar
  65. Weiman, C.F.R. 1989. Tracking algorithm using log-polar mapped image coordinates. In SPIE vol. 1192 Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, pp. 843-853.Google Scholar
  66. Youcef-Toumi, K. and Ito, O. 1990. A time delay controller for systems with unknown dynamics. Trans. ASME Journal of Dynamic Systems, Measurement, and Control, 112(1):133-142.Google Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Zeungnam Bien
  • Myung-Jin Chung
  • Pyung-Hun Chang
  • Dong-Soo Kwon
  • Dae-Jin Kim
  • Jeong-Su Han
  • Jae-Hean Kim
  • Do-Hyung Kim
  • Hyung-Soon Park
  • Sang-Hoon Kang
  • Kyoobin Lee
  • Soo-Chul Lim

There are no affiliations available

Personalised recommendations