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

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Intelligent Robotics and Applications (ICIRA 2015)

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

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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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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 .

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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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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

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22875-4

  • Online ISBN: 978-3-319-22876-1

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