Optimal design of a wheelchair-mounted robotic arm for activities of daily living.

Journal: Disability and rehabilitation. Assistive technology
Published Date:

Abstract

PURPOSE: The increasing prevalence of upper limb dysfunctions due to stroke, spinal cord injuries, and multiple sclerosis presents a critical challenge in assistive technology: designing robotic arms that are both energy‑efficient and capable of effectively performing activities of daily living (ADLs). This challenge is exacerbated by the need to ensure these devices are accessible for non‑expert users and can operate within the spatial constraints typical of everyday environments. Despite advancements in wheelchair‑mounted robotic arms (WMRAs), existing designs do not achieve an optimal balance-minimizing energy consumption and space while maximizing kinematic performance and workspace. Most robotic arms can perform a range of ADLs, but they do not account for outdoor environments where energy conservation is crucial. Furthermore, the need for WMRAs to be compact in idle configurations-essential for navigating through doors or between aisles-adds another layer of complexity to their design. This paper addresses these multifaceted design challenges by proposing a novel objective function to optimize the link lengths of WMRAs, aiming to reduce energy consumption without compromising the robots' operational capabilities.

Authors

  • Javier Dario Sanjuan De Caro
    Mechanical Engineering Department, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.
  • Md Samiul Haque Sunny
    Department of Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.
  • Gabriela Davila Albor
    Mechanical Engineering Department, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.
  • Tanvir Ahmed
    BioRobotics Laboratory, Mechanical/Biomedical Engineering Department, University of Wisconsin Milwaukee, Milwaukee, WI 53211, USA.
  • Md Mahbubur Rahman
    Department of Computer Science and Engineering, Jahangirnagar University, Savar, Dhaka.
  • Md Ishrak Islam Zarif
    Department of Computer Science, Marquette University, Milwaukee, WI, 53233, USA.
  • Asif Al Zubayer Swapnil
    Mechanical Engineering Department, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.
  • Inga Wang
    Department of Rehabilitation Sciences and Technology, University of Wisconsin-Milwaukee, Milwaukee, WI, 53211, USA.
  • Katie Schultz
    Clement J. Zablocki VA Medical Center, Milwaukee, WI, 53295, USA.
  • Sheikh Iqbal Ahamed
    Department of Computer Science, Marquette University, Milwaukee, WI, 53233, USA.
  • Mohammad H Rahman