Wheelchair Navigation: Automatically Adapting to Evolving Environments

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Abstract

Power wheelchairs can increase independence by supporting the mobility of their users. However, severe disabilities of users can render controlling the wheelchair difficult, if not impossible, especially over longer periods of time. This paper describes a proposal for research into techniques that would improve the experience and quality of life of wheelchair users by reducing the cognitive burden introduced by repetitive and complicated navigation tasks and manoeuvres. This will be achieved by sharing the control between the user and an autonomous controller. A number of techniques will be used to achieve this aim. Simultaneous Localisation and Mapping (SLAM) and topological mapping will be used for navigation between rooms while Computer Vision techniques will allow the (semi) automatic recognition of places in the user's home, based on the detection and categorisation of objects. Finally, medium to high level automation will be provided. This includes automatic and transparent assistance with tasks such as navigating through doorways but also autonomous navigation to specific locations using high level constructs ("take me to the kitchen table").
Original languageEnglish
Title of host publication20th Towards Autonomous Robotic Systems Conference
Subtitle of host publicationTAROS 2019
EditorsKaspar Althoefer, Jelizaveta Konstantinova, Ketao Zhang
PublisherSpringer Nature
Pages496-500
Number of pages5
Volume2
Edition1
ISBN (Electronic)978-3-030-25332-5
ISBN (Print)978-3030253318, 3030253317
DOIs
Publication statusPublished - 05 Jul 2019
Event20th Towards Autonomous Robotic Systems Conference: TAROS 2019 - Queen Mary University of London, London, United Kingdom of Great Britain and Northern Ireland
Duration: 03 Jul 201905 Jul 2019

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Nature
Volume11650
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th Towards Autonomous Robotic Systems Conference
Country/TerritoryUnited Kingdom of Great Britain and Northern Ireland
CityLondon
Period03 Jul 201905 Jul 2019

Keywords

  • Wheelchair
  • Shared Control
  • Computer Vision
  • SLAM
  • Middleware

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