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On-Line Estimation of Wheelchair Tire Slip Utilizing an Instantaneous Center of Rotation Extended Kalman Filter

[+] Author Affiliations
Kelilah Wolkowicz, Jesse Pentzer, Christopher Miller, Jason Z. Moore, Sean N. Brennan

Pennsylvania State University, University Park, PA

Paper No. DSCC2016-9699, pp. V001T06A002; 7 pages
doi:10.1115/DSCC2016-9699
From:
  • ASME 2016 Dynamic Systems and Control Conference
  • Volume 1: Advances in Control Design Methods, Nonlinear and Optimal Control, Robotics, and Wind Energy Systems; Aerospace Applications; Assistive and Rehabilitation Robotics; Assistive Robotics; Battery and Oil and Gas Systems; Bioengineering Applications; Biomedical and Neural Systems Modeling, Diagnostics and Healthcare; Control and Monitoring of Vibratory Systems; Diagnostics and Detection; Energy Harvesting; Estimation and Identification; Fuel Cells/Energy Storage; Intelligent Transportation
  • Minneapolis, Minnesota, USA, October 12–14, 2016
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5069-5
  • Copyright © 2016 by ASME

abstract

There are over three million wheelchair users within the United States and that number is growing. This paper is concerned with improving the safety of wheelchair operation by the on-line estimation of tire slip. Wheelchair tire slip is a result of icy or low friction surfaces, often representative of dangerous conditions. In this research, wheel slip is detected by estimating the instantaneous center of rotation (ICR) locations of wheelchair wheels relative to the ground surface. Any departure of the estimated ICR positions from the wheel contact point indicates slippage is occurring.

An Extended Kalman Filter (EKF) algorithm uses inputs of position and orientation obtained via map-based localization to detect changes in wheelchair ICR location estimates. The ICR EKF algorithm is verified in simulation. A robotic wheelchair is used for testing the presented algorithms under conditions inducing tire slip. The results show that the ICR locations do not vary significantly when the wheelchair is operated under normal conditions, i.e. low slip surfaces; however, they change significantly under slip conditions. Implementing this method with electric wheelchairs can improve the prediction of wheelchair motion on slippery surfaces, enabling warning systems and safe operational modes that can enhance the safety of wheelchair users.

Copyright © 2016 by ASME

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