Skip to main content

Evaluation of 3D obstacle avoidance algorithm for smart powered wheelchairs

Chatzidimitriadis, Sotirios and Oprea, Paul and Gillham, Michael and Sirlantzis, Konstantinos (2017) Evaluation of 3D obstacle avoidance algorithm for smart powered wheelchairs. In: 2017 Seventh International Conference on Emerging Security Technologies (EST). IEEE, pp. 157-162. ISBN 978-1-5386-4019-7. E-ISBN 978-1-5386-4018-0. (doi:10.1109/EST.2017.8090416)

PDF - Author's Accepted Manuscript
Download (1MB) Preview
[img]
Preview
Official URL
https://dx.doi.org/10.1109/EST.2017.8090416

Abstract

This research investigates the feasibility for the development of a novel 3D collision avoidance system for smart powered wheelchairs operating in a cluttered setting by using a scenario generated in a simulated environment using the Robot Operating System development framework. We constructed an innovative interface with a commercially available powered wheelchair system in order to extract joystick data to provide the input for interacting with the simulation. By integrating with a standard PWC control system the user can operate the PWC joystick with the model responding in real-time. The wheelchair model was equipped with a Kinect depth sensor segmented into three layers, two representing the upper body and torso, and a third layer fused with a LIDAR for the leg section. When using the assisted driving algorithm there was a 91.7% reduction in collisions and the course completion rate was 100% compared to 87.5% when not using the algorithm.

Item Type: Book section
DOI/Identification number: 10.1109/EST.2017.8090416
Uncontrolled keywords: wheelchairs; collision avoidance; robot senseing systems; three-dimensional displays; force; wheels; mathematical model
Divisions: Faculties > Sciences > School of Engineering and Digital Arts
Depositing User: Michael Gillham
Date Deposited: 14 Dec 2017 16:04 UTC
Last Modified: 26 Sep 2019 11:58 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/65458 (The current URI for this page, for reference purposes)
  • Depositors only (login required):

Downloads

Downloads per month over past year