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Multi-modal control framework for a semi-autonomous wheelchair using modular sensor designs

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Abstract

This paper presents the hardware and software control framework for a semi-auton omous wheelchair. The hardware design incorporates modular and reconfigurable sensors and corresponding low-level software architecture. Two control schemes are discussed. Assisted control that augments the user inputs by providing functionalities such as obstacle avoidance and wall following. And, semi-autonomous navigation which takes higher level destination goals and executes a simultaneous localization and mapping algorithm. We also propose an adaptive motion control with a online parameter estimation. The paper presents both experimental and simulation results.

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References

  1. Millan JR, Rupp R, Muller-Putz GR, Murray-Smith R, Giugliemma C, Tangermann M, Vidaurre C, Cincotti F, Kübler A, Leeb R, Neuper C, Müller K-R, Mattia D (2010) Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges. Front Neurosci 4:161. doi:10.3389/fnins.2010.00161

    Google Scholar 

  2. Simpson RC (July 2005) Smart wheelchairs: a literature review. J Rehabil Res Dev 42(4):423–438

    Google Scholar 

  3. Kulyukin V, Gharpure C, Nicholson J (2005) Robocart: toward robot-assisted navigation of grocery stores by the visually impaired. In: Intelligent Robots and Systems, (IROS 2005), 2005 IEEE/RSJ International Conference on, pp. 2845–2850

  4. Tsui KM, Feil-Seifer DJ, Mataric MJ, Yanco HA (2009) Performance evaluation methods for assistive robotic technology. In: Madhavan R, Tunstel E, Messina E (eds) Performance evaluation and benchmarking of intelligent systems. Springer, US, pp 41–66

    Chapter  Google Scholar 

  5. Krebs HI (2003) Rehabilitation robotics: performance-based progressive robot-assisted therapy. Auton Robots 15:720

    Article  Google Scholar 

  6. Tsui KM, Yanco HA, Feil-Seifer DJ, Mataric MJ (2008) Survey of domain-specific performance measures in assistive robotic technology. In: Proceedings of the 8th workshop on performance metrics for intelligent systems, PerMIS’08, ACM, New York, NY, USA, pp. 116–123

  7. Buhler Ch, Hoelper R, Hoyer H, Humann W (1995) Autonomous robot technology for advanced wheelchair and robotic aids for people with disabilities. Rob Auton Syst 14(2–3):213–222

    Article  Google Scholar 

  8. Alqasemi R, Dubey R (2009) Kinematics, control and redundancy resolution of a 9-dof wheelchair-mounted robotic arm system for ADL tasks. In: Mechatronics and its applications, 2009. ISMA 09. 6th International Symposium on, pp. 1–7

  9. Yanco H (1998) Wheelesley: a robotic wheelchair system: indoor navigation and user interface. In: Mittal V, Yanco H, Aronis J, Simpson R (eds) Assistive Technology and Artificial Intelligence, vol 1458, Lecture Notes in Computer Science. Springer, Berlin / Heidelberg, pp 256–268

  10. Parikh SP, Grassi V Jr, Kumar V, Jr JO (2007) Integrating human inputs with autonomous behaviours on an intelligent wheelchair platform. Intell Syst IEEE 22(2):33–41

    Article  Google Scholar 

  11. Perrin X, Chavarriaga R, Colas F, Siegwart R, Millan JR (2010) Brain-coupled interaction for semi-autonomous navigation of an assistive robot. Rob Auton Syst 58(12):1246–1255. Intelligent Robotics and Neuroscience

    Google Scholar 

  12. Iturrate I, Antelis JM, Kubler A, Minguez J (June 2009) A noninvasive brain-actuated wheelchair based on a P300 neurophysiological protocol and automated navigation. Rob IEEE Trans 25(3):614–627

  13. Kossiakoff A, Sweet WN, Seymour SJ, Biemer SM (2003) Systems engineering: principles and practice, 2nd edn. Wiley, London

    Google Scholar 

  14. Palacin J, Valganon I, Pernia R (2006) The optical mouse for indoor mobile robot odometry measurement. Sens Actuators A Phys 126(1):141–147

    Article  Google Scholar 

  15. Nistr D, Naroditsky O, Bergen J (2004) “Visual odometry”, in Computer Vision and Pattern Recognition, 2004. CVPR 2004. In: Proceedings of the 2004 IEEE computer society conference on, vol. 1, p. I652

  16. Quigley M, Gerkey B, Conley K, Faust J, Foote T, Leibs J, Berger E, Wheeler R, Ng A (2009) ROS: an open-source Robot Operating System. In: ICRA workshop on open source software, vol. 3

  17. Nezamfar H, Sinyukov D, Orhan U, Erdogmus D, Padir T (2013) Rain interface to control a tele-operated robot. In: Proceedings of the fifth international brain-computer interface meeting, June 2013

  18. Kohlbrecher S, von Stryk O, Meyer J, Klingauf U (2011) A flexible and scalable SLAM system with full 3D motion estimation. In: 2011 IEEE international symposium on safety, security, and rescue robotics (SSRR), pp 155–160

  19. Dijkstra EW (1959) A note on two problems in connexion with graphs. Numerische mathematik 1(1):269–271

    Article  MATH  MathSciNet  Google Scholar 

  20. von Hundelshausen F, Himmelsbach M, Hecker F, Mueller A, Wuensche HJ (2008) Driving with tentacles: integral structures for sensing and motion. J Field Rob 25(9):640–673

    Article  Google Scholar 

  21. Astrom KJ, Wittenmark B (1994) Adaptive control. Addison-Wesley Longman Publishing Co., Inc., Boston, MA

    Google Scholar 

  22. Johnson BW, Aylor JH (1985) Dynamic modeling of an electric wheelchair. IEEE Trans Ind Appl IA–21(5):1284–1293

    Article  Google Scholar 

Download references

Acknowledgments

This material is based upon work supported by the National Science Foundation under Grant No. 1135854.

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Correspondence to Dmitry Sinyukov.

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Sinyukov, D., Desmond, R., Dickerman, M. et al. Multi-modal control framework for a semi-autonomous wheelchair using modular sensor designs. Intel Serv Robotics 7, 145–155 (2014). https://doi.org/10.1007/s11370-014-0149-7

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