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International Conference on Intelligent Robotics and Applications

ICIRA 2015: Intelligent Robotics and Applications pp 260–271Cite as

Shared Control of an Intelligent Wheelchair with Dynamic Constraints Using Brain-Machine Interface

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9245))

Abstract

In this paper, a human-machine shared control strategy is developed for the navigation of a wheelchair. The shared controller switches between a brain-machine control mode and an autonomous control mode. In the brain-machine control mode, a novel brain-machine interface (BMI) using only two command signals produced by steady state visual evoked potentials (SSVEP) instead of traditional four-direction command signals is developed. These two brain signals are involved to generate a polar polynomial trajectory (PPT), which is continuous in curvature without violating dynamic constraints of the wheelchair. In the autonomous control mode, the synthesis of angle-based potential field (APF) and vision-based simultaneous localization and map-building (SLAM) technique is proposed to guide the robot navigating in environments where obstacles exist. Experimental studies have been carried out with a number of volunteers and the effectiveness of the proposed shared control scheme has been verified.

This work was supported in part by EPSRC grant EP/L026856/1,Guangdong Provincial Natural Science Foundation of China under Grant 2014A030313266, the Fundamental Research Funds for the Central Universities under Grant 2015ZM065, and National Natural Science Foundation of China under Grants 61473120 and 61473038.

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References

  1. Leishman, F., Horn, O., Bourhis, G.: Smart wheelchair control through a deictic approach. Robotics and Autonomous Systems 58, 1149–1158 (2010)

    Article  Google Scholar 

  2. Poncela, A., Urdiales, C., Pérez, E.J., Sandoval, F.: A new efficiency-weighted strategy for continuous human/robot cooperation in navigation. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans 39, 486–500 (2009)

    Article  Google Scholar 

  3. Sheridan, T.B.: Telerobotics, Automation, and Human Supervisory Control. The MIT Press. Cop., Cambridge (1992)

    Google Scholar 

  4. Scherer, R., Faller, J., Balderas, D., Friedrich, E.V.C., Proll, M., Allison, B.: Brain computer interfacing: more than the sum of its parts. Soft Comput. 17(2), 317–331 (2013)

    Article  Google Scholar 

  5. Schalk, G., Miller, K.J., Anderson, N.R., Wilson, J.A., Smyth, M.D., Ojemann, J.G.: Two-dimensional movement control using electrocorticographic signals in humans. J. Neural. Eng. 5(1), 75–84 (2008)

    Article  Google Scholar 

  6. Vidaurre, C., Schlogl, A., Cabeza, R., Scherer, R., Pfurtscheller, G.: Study of on-line adaptive discriminant analysis for EEG-based brain computer interfaces. IEEE Trans. Biomed. Eng. 54(3), 550–556 (2007)

    Article  Google Scholar 

  7. Acir, N., Oztura, I., Kuntalp, M., Baklan, B., Guzelis, C.: Automatic detection of epileptiform events in EEG by a three-stage procedure based on artificial neural networks. IEEE Transactions on Biomedical Engineering 52(1), 30–40 (2005)

    Article  Google Scholar 

  8. Pregenzer, M., Pfurtscheller, G.: Frequency component selection for an EEG-based brain to computer interface. IEEE Transactions on Rehabilitation Engineering 7(4), 413–419 (1999)

    Article  Google Scholar 

  9. Megevand, P., Quairiaux, C., Lascano, A.M., Kiss, J.Z., Michel, C.M.: A mouse model for studying large-scale neuronal networks using EEG mapping techniques. NeuroImage 42, 591–602 (2008)

    Article  Google Scholar 

  10. Benz, H.L., Zhang, H., Bezerianos, A., Acharya, S., Crone, N.E., Zheng, X., Thakor, N.V.: Connectivity analysis as a novel approach to motor decoding for prosthesis control. IEEE Trans. Neural Networks and Learning Systems 20(2), 143–152 (2012)

    Google Scholar 

  11. Levine, S., Bell, D., Jaros, A., Simpsons, R., Koren, Y., Borenstein, J.: The NavChair assistive wheelchair navigation system. IEEE Transactions on Rehabilitation Engineering 7, 443–451 (1999)

    Article  Google Scholar 

  12. Nelson, W.: Continuous-curvature paths for autonomous vehicles. In: Proceedings of 1989 IEEE International Conference on Robotics and Automation, vol. 3, pp. 1260–1264, May 1989

    Google Scholar 

  13. Pinchard, O., Liegeois, A., Pougnet, F.: Generalized polar polynomials for vehicle path generation with dynamic constraints. In: Proceedings of 1996 IEEE International Conference on Robotics and Automation, vol. 1, pp. 915–920, April 1996

    Google Scholar 

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Author information

Authors and Affiliations

  1. Key Lab of Autonomous System and Network Control and College of Automation Science and Engineering, South China University of Technology, Guangzhou, China

    Z. Li, C. Yang, S. Zhao & C.-Y. Su

  2. Center for Robotics and Neural Systems, Plymouth University, Plymouth, UK

    C. Yang & N. Wang

  3. Department of Mechanical and Industrial Engineering, Concordia University, Montreal, Canada

    C.-Y. Su

Authors
  1. Z. Li
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  2. C. Yang
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  3. S. Zhao
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  4. N. Wang
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  5. C.-Y. Su
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Corresponding author

Correspondence to C. Yang .

Editor information

Editors and Affiliations

  1. University of Portsmouth, Portsmouth, United Kingdom

    Honghai Liu

  2. Tokyo Metropolitan University, Tokyo, Japan

    Naoyuki Kubota

  3. Shanghai Jiao Tong University, Shanghai, China

    Xiangyang Zhu

  4. Karlsruhe Institute of Technology, Karlsruhe, Germany

    Rüdiger Dillmann

  5. University of Portsmouth, Portsmouth, United Kingdom

    Dalin Zhou

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© 2015 Springer International Publishing Switzerland

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Li, Z., Yang, C., Zhao, S., Wang, N., Su, CY. (2015). Shared Control of an Intelligent Wheelchair with Dynamic Constraints Using Brain-Machine Interface. In: Liu, H., Kubota, N., Zhu, X., Dillmann, R., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2015. Lecture Notes in Computer Science(), vol 9245. Springer, Cham. https://doi.org/10.1007/978-3-319-22876-1_23

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  • DOI: https://doi.org/10.1007/978-3-319-22876-1_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22875-4

  • Online ISBN: 978-3-319-22876-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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