Automated Curb Recognition and Negotiation for Robotic Wheelchairs
| Autor: | Sivashankar Sivakanthan, Satish Andrea Sundaram, Rory A. Cooper, Ella M. Atkins, Jie Zhou, Jorge Candiotti, Jeremy D. Castagno |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Computer science
media_common.quotation_subject Reliability (computer networking) Human error Extraction algorithm TP1-1185 Biochemistry Article Analytical Chemistry Rehabilitation engineering Wheelchair Robotic Surgical Procedures Human–computer interaction obstacle negotiation Humans Electrical and Electronic Engineering Instrumentation media_common step-climbing wheelchair rehabilitation engineering Negotiating Chemical technology Reproducibility of Results Equipment Design Robotics Atomic and Molecular Physics and Optics Negotiation Wheelchairs Robot Powered wheelchairs |
| Zdroj: | Sensors (Basel, Switzerland) Sensors; Volume 21; Issue 23; Pages: 7810 Sensors, Vol 21, Iss 7810, p 7810 (2021) |
| ISSN: | 1424-8220 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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