Cargando…

Automated Curb Recognition and Negotiation for Robotic Wheelchairs

Common electric powered wheelchairs cannot safely negotiate architectural barriers (i.e., curbs) which could injure the user and damage the wheelchair. Robotic wheelchairs have been developed to address this issue; however, proper alignment performed by the user is needed prior to negotiating curbs....

Descripción completa

Detalles Bibliográficos
Autores principales: Sivakanthan, Sivashankar, Castagno, Jeremy, Candiotti, Jorge L., Zhou, Jie, Sundaram, Satish Andrea, Atkins, Ella M., Cooper, Rory A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659845/
https://www.ncbi.nlm.nih.gov/pubmed/34883815
http://dx.doi.org/10.3390/s21237810
_version_ 1784613061481463808
author Sivakanthan, Sivashankar
Castagno, Jeremy
Candiotti, Jorge L.
Zhou, Jie
Sundaram, Satish Andrea
Atkins, Ella M.
Cooper, Rory A.
author_facet Sivakanthan, Sivashankar
Castagno, Jeremy
Candiotti, Jorge L.
Zhou, Jie
Sundaram, Satish Andrea
Atkins, Ella M.
Cooper, Rory A.
author_sort Sivakanthan, Sivashankar
collection PubMed
description Common electric powered wheelchairs cannot safely negotiate architectural barriers (i.e., curbs) which could injure the user and damage the wheelchair. Robotic wheelchairs have been developed to address this issue; however, proper alignment performed by the user is needed prior to negotiating curbs. Users with physical and/or sensory impairments may find it challenging to negotiate such barriers. Hence, a Curb Recognition and Negotiation (CRN) system was developed to increase user’s speed and safety when negotiating a curb. This article describes the CRN system which combines an existing curb negotiation application of a mobility enhancement robot (MEBot) and a plane extraction algorithm called Polylidar3D to recognize curb characteristics and automatically approach and negotiate curbs. The accuracy and reliability of the CRN system were evaluated to detect an engineered curb with known height and 15 starting positions in controlled conditions. The CRN system successfully recognized curbs at 14 out of 15 starting positions and correctly determined the height and distance for the MEBot to travel towards the curb. While the MEBot curb alignment was 1.5 ± 4.4°, the curb ascending was executed safely. The findings provide support for the implementation of a robotic wheelchair to increase speed and reduce human error when negotiating curbs and improve accessibility.
format Online
Article
Text
id pubmed-8659845
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-86598452021-12-10 Automated Curb Recognition and Negotiation for Robotic Wheelchairs Sivakanthan, Sivashankar Castagno, Jeremy Candiotti, Jorge L. Zhou, Jie Sundaram, Satish Andrea Atkins, Ella M. Cooper, Rory A. Sensors (Basel) Article Common electric powered wheelchairs cannot safely negotiate architectural barriers (i.e., curbs) which could injure the user and damage the wheelchair. Robotic wheelchairs have been developed to address this issue; however, proper alignment performed by the user is needed prior to negotiating curbs. Users with physical and/or sensory impairments may find it challenging to negotiate such barriers. Hence, a Curb Recognition and Negotiation (CRN) system was developed to increase user’s speed and safety when negotiating a curb. This article describes the CRN system which combines an existing curb negotiation application of a mobility enhancement robot (MEBot) and a plane extraction algorithm called Polylidar3D to recognize curb characteristics and automatically approach and negotiate curbs. The accuracy and reliability of the CRN system were evaluated to detect an engineered curb with known height and 15 starting positions in controlled conditions. The CRN system successfully recognized curbs at 14 out of 15 starting positions and correctly determined the height and distance for the MEBot to travel towards the curb. While the MEBot curb alignment was 1.5 ± 4.4°, the curb ascending was executed safely. The findings provide support for the implementation of a robotic wheelchair to increase speed and reduce human error when negotiating curbs and improve accessibility. MDPI 2021-11-24 /pmc/articles/PMC8659845/ /pubmed/34883815 http://dx.doi.org/10.3390/s21237810 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sivakanthan, Sivashankar
Castagno, Jeremy
Candiotti, Jorge L.
Zhou, Jie
Sundaram, Satish Andrea
Atkins, Ella M.
Cooper, Rory A.
Automated Curb Recognition and Negotiation for Robotic Wheelchairs
title Automated Curb Recognition and Negotiation for Robotic Wheelchairs
title_full Automated Curb Recognition and Negotiation for Robotic Wheelchairs
title_fullStr Automated Curb Recognition and Negotiation for Robotic Wheelchairs
title_full_unstemmed Automated Curb Recognition and Negotiation for Robotic Wheelchairs
title_short Automated Curb Recognition and Negotiation for Robotic Wheelchairs
title_sort automated curb recognition and negotiation for robotic wheelchairs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659845/
https://www.ncbi.nlm.nih.gov/pubmed/34883815
http://dx.doi.org/10.3390/s21237810
work_keys_str_mv AT sivakanthansivashankar automatedcurbrecognitionandnegotiationforroboticwheelchairs
AT castagnojeremy automatedcurbrecognitionandnegotiationforroboticwheelchairs
AT candiottijorgel automatedcurbrecognitionandnegotiationforroboticwheelchairs
AT zhoujie automatedcurbrecognitionandnegotiationforroboticwheelchairs
AT sundaramsatishandrea automatedcurbrecognitionandnegotiationforroboticwheelchairs
AT atkinsellam automatedcurbrecognitionandnegotiationforroboticwheelchairs
AT cooperrorya automatedcurbrecognitionandnegotiationforroboticwheelchairs