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A Decision-Theoretic Approach for the Collaborative Control of a Smart Wheelchair

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Abstract

While assistive robot technology is quickly progressing, several challenges remain to make this technology truly usable and useful for humans. One of the aspects that is particularly important is in defining control protocols that allow both the human and the robot technology to contribute to the best of their abilities. In this paper we propose a framework for the collaborative control of a smart wheelchair designed for individuals with mobility impairments. Our approach is based on a decision-theoretic model of control, and accepts commands from both the human user and robot controller. We use a Partially Observable Markov Decision Process to optimize the collaborative action choice, which allows the system to take into account uncertainty in the user intent, in the command and in the environment. The system is deployed and validated on the SmartWheeler platform, and experiments with 8 users show the improvement in usability and navigation efficiency that are achieved with this form of collaborative control.

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Notes

  1. http://wiki.ros.org/move_base.

  2. http://www.wheelchairskillsprogram.ca/eng/documents/FORM_WST-P-WCU_4.2.1_approved.pdf.

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Acknowledgements

Funding for this project was provided through the NSERC Canadian Field Robotics Network (NCFRN), the NSERC Discovery program and the AGE-WELL NCE. Many thanks to Martin Gerdzhev, Alan Do-Omri, Anne-Marie Hébert and Dahlia Kairy for helpful suggestions throughout the experimental phase of the work.

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Authors and Affiliations

  1. Department of Electrical Engineering, Polytechnique Montreal, Montreal, Canada

    Mahmoud Ghorbel & Richard Gourdeau

  2. School of Computer Science, McGill University, Montreal, Canada

    Joelle Pineau

  3. Carnegie Mellon University, Pittsburgh, PA, USA

    Shervin Javdani & Siddhartha Srinivasa

Authors
  1. Mahmoud Ghorbel
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  2. Joelle Pineau
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  3. Richard Gourdeau
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  4. Shervin Javdani
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  5. Siddhartha Srinivasa
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Corresponding authors

Correspondence to Mahmoud Ghorbel or Joelle Pineau.

Appendices

Appendix A: Theorem Demonstration

We detail in this paragraph the mathematical proof (by reverse induction) of the Eqs. (15, 16):

Proof

At the final time T,

We seek to minimize our cost for the final destination at all time, so \(\forall t \,\,\,\, \forall \kappa \, \mathcal {V}_g^{t}(x) \leqslant \mathcal {V}^{t}_{\kappa }(x) \), then \( \mathcal {V}_g^{t}(x) \leqslant \underset{\kappa }{min} \, \mathcal {V}^{t}_{\kappa }(x) \) Finally

We assume that our equations are true for t,

Our proof is complete. \(\square \)

Appendix B: Wheelchaire Skills Test

figure a

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Ghorbel, M., Pineau, J., Gourdeau, R. et al. A Decision-Theoretic Approach for the Collaborative Control of a Smart Wheelchair. Int J of Soc Robotics 10, 131–145 (2018). https://doi.org/10.1007/s12369-017-0434-7

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