Anti-collision and Navigation Systems for Powered Wheelchairs
Keywords: Anti-collision, cognitive impairments, intelligent wheelchair, older adults, physical disability
In collaboration with: The Laboratory for Computational Intelligence, University of British Colombia and the School of Computing, University of Dundee
Overview of Research
Older adults who have lost their ability to walk often rely on wheelchairs for their mobility. Adults who lack the physical strength to use manual wheelchairs are given powered wheelchairs, but only if they have the memory and judgment required to safely operate one. These necessary skills are often limited in adults who have cognitive impairments. As a result, cognitively impaired adults who are in need of powered wheelchairs are unable to obtain them and must rely on others for mobility. Independent mobility has been linked to quality of life and a decrease in mobility contributes to a decrease in quality of life [1].
This project aims to provide a safe and intuitive means of mobility for individuals who have cognitive impairments. To accomplish this goal an Intelligent Wheelchair System is proposed. This system will have four main features:
- The ability to assist a cognitively impaired individual with navigation through the use of audio prompts.
- An anti-collision system to prevent injury to the user and bystanders.
- A shared control approach where the system will aid the user with navigation according to user’s preferences/intents.
- The ability to add-on to existing powered wheelchairs.
Anti-collision protection is paramount when dealing with older adults. Studies have shown that a fall is the most probable outcome after being hit by a wheelchair. Falls for elderly individuals could have severe consequences such as hip fractures, which may even lead to death [2].
To accomplish the navigation and anti-collision objectives a stereovision camera (Figure 1) is mounted on the wheelchair and is used as an input to the Intelligent Wheelchair System. Images from the camera are used to compute the distance of objects from the wheelchair. This distance reading is used to prevent objects from getting too close to the wheelchair, thus avoiding collisions (Figure 2). The distance reading is also translated to an occupancy grid (Figure 3), which is used by the system to determine the least obstructed routes around objects.
Current research on this project includes development of:
- Developing hardware for the system into a user-friendly form;
- Improving anti-collision algorithms to have better detection of the environment;
- Improving planning/mapping algorithms to incorporate the user's schedule/preferences;
- Clinical trials with older adults with dementia.
Read more about the project's technical details.
Figure 1: Powered Wheelchair with Intelligent Wheelchair System (stereovision camera in blue).
Figure 2: [Left] Distance readings, where brighter objects are closer to the wheelchair; [Right] Anti-collision system detects a close object (Click on image to enlarge).
Figure 3: Images from camera and corresponding occupancy grid (Click on image to enlarge).
Research Team
Alex Mihailidis, PhD, PEng (University of Toronto)
Jim Little, PhD (University of British Colombia)
Alan Mackworth, PhD (University of British Colombia)
Jesse
Hoey, PhD (University of Dundee)
Tuck-Voon How, MASc (University of Toronto)
Rosalie Wang, Post-Doctoral Fellow (University of Toronto)
Pooja Viswanathan,
PhD candidate (University of British Colombia)
Funding
IATSL is a member of the CANWHEEL team. CANWHEEL is a CIHR-funded research program aimed to improve the mobility of older adult wheelchair users by enabling power wheelchair use in those who are normally excluded from use of these devices.
References
- Mihailidis, A., Elinas, P., Boger, J. and Hoey, J.
(2007). An Intelligent Powered Wheelchair to Enable Mobility of Cognitively
Impaired Older Adults: An Anti-Collision System. IEEE Transactions
on Neural Systems & Rehabilitation Engineering, 15(1), 136-143.
- Viswanathan, P., Boger, J., Hoey, J., Elinas, P. and Mihailidis, A. (2007). The Future of Wheelchairs: Intelligent Collision Avoidance and Navigation Assistance. Geriatrics and Aging Magazine, 10(4), 253–256.
Related Work
- Wang, R. H., Mihailidis, A., Dutta, T. and Fernie, G. R. (in review, 2010). Usability testing of a multimodal feedback interface on a simulated collision-avoidance power wheelchair for long-term care home residents with cognitive impairments. Journal of Rehabilitation Research and Development.
- How, T.V. and Mihailidis, A. (in review, 2010). Clinical Evaluation of the Intelligent Wheelchair System. Festival of Intl Conf on Caregiving, Disability, Aging and Technology (FICCDAT): The 3rd Intl Conf on Technology and Aging (ICTA), Toronto, Canada, 2011.
- How, T. and Mihailidis, A. (May 2010). Anti-collision and navigation system for powered wheelchairs. Gerontechnology, 9(2), 289; Vancouver, BC. doi:10.4017/gt.2010.09.02.138.00
