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A Position Detecting System Using Supersonic Sensors for Omnidirectional Wheelchair Tennis

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Advances in Network-Based Information Systems (NBiS 2018)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 22))

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Abstract

The wheelchair with good performance for the aged and disabled is attracting attention from the society. Also, the wheelchair can provide the user with many benefits, such as maintaining mobility, continuing or broadening community social activities, conserving energy and enhancing quality of life. The wheelchair body must be compact enough and should be able to make different movements in order to have many applications. In our previous work, we presented the design and implementation of an omnidirectional wheelchair. In this paper, we propose a position detecting system using supersonic sensors. The proposed system can find correctly the wheelchair position for collision avoidance.

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References

  1. Arai, K., Mardiyanto, R.: A prototype of electric wheelchair controlled by eye-only for paralyzed user. J. Robot. Mechatron. 23(1), 66–74 (2011)

    Article  Google Scholar 

  2. Carlson, T., Demiris, Y.: Collaborative control for a robotic wheelchair: evaluation of performance, attention, and workload. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 42(3), 876–888 (2012)

    Google Scholar 

  3. Diez, P.F., Mut, V.A., Perona, E.M.A., Leber, E.L.: Asynchronous BCI control using high-frequency SSVEP. J. Neuroeng. Rehabil. 8(1), 1–8 (2011). http://www.jneuroengrehab.com/content/8/1/39

  4. Escobedo, A., Spalanzani, A., Laugier, C.: Multimodal control of a robotic wheelchair: using contextual information for usability improvement. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems 2013, pp. 4262–4267 (2013)

    Google Scholar 

  5. Furuno, Y., Tanaka, Y., Nakatoh, Y.: Detecting system of approaching vehicles using an ultrasonic wave. In: Consumer Electronics (ICCE) on IEEE International Conference, pp. 393–394 (2016)

    Google Scholar 

  6. Gonzalez, J., Muaeoz, A., Galindo, C., Fernandez-Madrigal, J., Blanco, J.: A description of the SENA robotic wheelchair. In: Proceedings of the IEEE Mediterranean Electrotechnical Conference (MELECON-2006), pp. 437–440 (2006)

    Google Scholar 

  7. Gray, J., Jia, P., Hu, H.H., Lu, T., Yuan, K.: Head gesture recognition for hands-free control of an intelligent wheelchair. Ind. Robot Int. J. 34(1), 60–68 (2007)

    Article  Google Scholar 

  8. Grigorescu, S.M., Lüth, T., Fragkopoulos, C., Cyriacks, M., Gräser, A.: A BCI-controlled robotic assistant for quadriplegic people in domestic and professional life. Robotica 30(03), 419–431 (2012)

    Article  Google Scholar 

  9. Ishida, S., Miyamoto, H.: Collision-detecting device for omnidirectional electric wheelchair. ISRN Robot. 2013, 1–8 (2012)

    Google Scholar 

  10. Kobayashi, Y., Kinpara, Y., Shibusawa, T., Kuno, Y.: Robotic wheelchair based on observations of people using integrated sensors. In: IROS, pp. 2013–2018 (2009)

    Google Scholar 

  11. Lu, T., Yuan, K., Zhu, H.: Research status and development trend of intelligent wheelchair. Appl. Technol. Robot 2, 1–5 (2008)

    Google Scholar 

  12. Matsuo, K., Barolli, L.: Design and implementation of an omnidirectional wheelchair: control system and its applications. In: Proceedings of the 9th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA-2014), pp. 532–535 (2014)

    Google Scholar 

  13. Matsuo, K., Liu, Y., Elmazi, D., Barolli, L., Uchida, K.: Implementation and evaluation of a small size omnidirectional wheelchair. In: Proceedings of the IEEE 29th International Conference on Advanced Information Networking and Applications Workshops (WAINA-2015), pp. 49–53 (2015)

    Google Scholar 

  14. Mori, Y., Sakai, N., Katsumura, K.: Development of a wheelchair with a lifting function. Adv. Mech. Eng. 2012, 1–9 (2012)

    Google Scholar 

  15. Thong-un, N., Hirata, S., Orino, Y., Kurosawa, M.K.: A linearization-based method of simultaneous position and velocity measurement using ultrasonic waves. Sens. Actuators A Phys. 233, 480–499 (2015)

    Article  Google Scholar 

  16. Wang, H., Grindle, G.G., Candiotti, J., Chung, C., Shino, M., Houston, E., Cooper, R.A.: The personal mobility and manipulation appliance (PerMMA): a robotic wheelchair with advanced mobility and manipulation. In: 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 3324–3327 (2012)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology (FIT), 3-30-1 Wajiro-Higashi, Higashi-Ku, Fukuoka, 811-0295, Japan

    Keita Matsuo & Leonard Barolli

Authors
  1. Keita Matsuo
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  2. Leonard Barolli
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Corresponding author

Correspondence to Keita Matsuo .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Faculty of Management, Comenius University in Bratislava, Bratislava, Slovakia

    Natalia Kryvinska

  3. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

  4. Department of Advanced Sciences, Hosei University, Tokyo, Japan

    Makoto Takizawa

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Matsuo, K., Barolli, L. (2019). A Position Detecting System Using Supersonic Sensors for Omnidirectional Wheelchair Tennis. In: Barolli, L., Kryvinska, N., Enokido, T., Takizawa, M. (eds) Advances in Network-Based Information Systems. NBiS 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-98530-5_6

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