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Modular and Adaptive Wheelchair Automation

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Book cover Experimental Robotics

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 109))

Abstract

We present in this paper a novel framework for the design of a modular and adaptive partial-autonomy wheelchair. Our design in particular aims to address hurdles to the adoption of partial-autonomy wheelchairs within general society. In this experimental work, a single assistance module (assisted doorway traversal) is evaluated, with arbitration between multiple goals (from multiple detected doors) and multiple control signals (from an autonomous path planner, and the human user). The experimental work provides the foundation and proof-of-concept for the technical components of our proposed modular and adaptive wheelchair robot. The system is evaluated within multiple environmental scenarios and shows good performance.

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Notes

  1. 1.

    Exceptions include the Smart Wheelchair from Smile Rehab [11] and TAO-7 Intelligent Wheelchair Base from AAI Canada [12].

  2. 2.

    Including: the Q-Logic system from Pride Mobility; PG Drive Systems’ R-Net electronics system used by Permobil, Pride Mobility, and Sunrise Medical; and the MK6i electronics system used by Invacare [34, 35].

  3. 3.

    Full specifications: mini-PC = Shuttle XH61 mini-PC with Intel i7-2600S processor, 16GB DDR3 SDRAM, 40GB solid state hard drive; IR range sensor = Sharp GP2Y0A02YK IR distance sensors (\(\times 10\)); Ultra-sonic range sensor = Maxbotix LV-MaxSonar-EZ1 Ultra-sonic range sensors (\(\times 4\)); Sensor interface board = Arduino Mega2560. Total cost: \(\$1070\).

  4. 4.

    Implementation of the adaptation components of our framework are currently under development, and are not included in this assessment.

  5. 5.

    Since d and \(\phi \) are both always positive, the logistic function (fractions in parentheses) range is [0, 0.5]. The factor of 2 in this equation compensates for this fact, so that the range of \(c_g\) becomes [0, 1].

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Acknowledgments

Many thanks to Matthew Derry for his significant contributions to the development of the software infrastructure for this system.

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Authors and Affiliations

  1. Northwestern University, Evanston, IL, 60208, USA

    Brenna D. Argall

  2. Rehabilitation Institute of Chicago, Chicago, IL, 60211, USA

    Brenna D. Argall

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  1. Brenna D. Argall
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Correspondence to Brenna D. Argall .

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Editors and Affiliations

  1. Drexel University, Philadelphia, Pennsylvania, USA

    M. Ani Hsieh

  2. Department of Computer Science, Stanford University, Stanford, California, USA

    Oussama Khatib

  3. Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Vijay Kumar

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Argall, B.D. (2016). Modular and Adaptive Wheelchair Automation. In: Hsieh, M., Khatib, O., Kumar, V. (eds) Experimental Robotics. Springer Tracts in Advanced Robotics, vol 109. Springer, Cham. https://doi.org/10.1007/978-3-319-23778-7_55

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  • DOI: https://doi.org/10.1007/978-3-319-23778-7_55

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