Abstract
A smart wheelchair was developed to provide users with increased independence and flexibility in their lives. The wheelchair can be operated in a fully autonomous mode or a hybrid brain-controlled mode while the continuously running autonomous mode may override the user-generated motion command to avoid potential dangers. The wheelchair’s indoor mobility has been demonstrated by operating it in a dynamically occupied hallway, where the smart wheelchair intelligently interacted with pedestrians. An extended operation of the wheelchair for outdoor environments was also explored. Terrain recognition based on visual image processes and multi-layer neural learning network was demonstrated. A mounted Laser Range Finder (LRF) was used to determine terrain drop-offs and steps and to detect stationary and moving obstacles for autonomous path planning. Real-time imaging of the outdoor scenes using the oscillating LRF was attempted; however, the overhead in generating a three-dimensional point cloud exceeded the onboard computer capability.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Callahan, M.: Mind-Controlled Wheelchair. PN (Paraplegia News) Magazine 61(8) (August 2007)
BSI-Toyota Collaboration Center (BTCC): Real-time control of wheelchairs with brain waves. TOYOTA News Release, June 29 (2009)
Iturrate, I., Antelis, J.M., Kuebler, A., Minguez, J.: A Noninvasive Brain-Actuated Wheelchair Based on a P300 Neurophysiological Protocol and Automated Navigation. IEEE Transaction on Robotics 25(3) (June 2009)
Lin, C.T.: A Non-Invasive Brain-Computer Interface for Autonomous Wheelchair Mobility. In: 26th Annual International Technology and Persons with Disabilities Conference, San Diego, California, March 14-19 (2011)
Lin, C.T., Euler, C., Mekhtarian, A., Gil, A., Hern, L., Prince, D., Shen, Y., Horvath, J.: A Brain-Computer Interface for Intelligent Wheelchair Mobility. In: Pan American Health Care Exchanges (PAHCE) 2011 Conference, IEEE, Paper No. 201, Rio de Janeiro, Brazil, March 28-April 1 (2011)
Lin, C.T., Euler, C., Wang, P., Mekhtarian, A., Horvath, J.: Improved and Extended Mobility and Machine Learning for an Intelligent Wheelchair. In: 27th Annual International Technology and Persons with Disabilities Conference, San Diego, California, February 27-March 2 (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lin, C.T., Euler, C., Wang, PJ., Mekhtarian, A. (2012). Indoor and Outdoor Mobility for an Intelligent Autonomous Wheelchair. In: Miesenberger, K., Karshmer, A., Penaz, P., Zagler, W. (eds) Computers Helping People with Special Needs. ICCHP 2012. Lecture Notes in Computer Science, vol 7383. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31534-3_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-31534-3_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31533-6
Online ISBN: 978-3-642-31534-3
eBook Packages: Computer ScienceComputer Science (R0)