Back to Search Start Over

Obstacle avoidance for power wheelchair using bayesian neural network.

Authors :
Trieu HT
Nguyen HT
Willey K
Source :
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2007; Vol. 2007, pp. 4771-4.
Publication Year :
2007

Abstract

In this paper we present a real-time obstacle avoidance algorithm using a Bayesian neural network for a laser based wheelchair system. The raw laser data is modified to accommodate the wheelchair dimensions, allowing the free-space to be determined accurately in real-time. Data acquisition is performed to collect the patterns required for training the neural network. A Bayesian frame work is applied to determine the optimal neural network structure for the training data. This neural network is trained under the supervision of the Bayesian rule and the obstacle avoidance task is then implemented for the wheelchair system. Initial results suggest this approach provides an effective solution for autonomous tasks, suggesting Bayesian neural networks may be useful for wider assistive technology applications.

Details

Language :
English
ISSN :
2375-7477
Volume :
2007
Database :
MEDLINE
Journal :
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Publication Type :
Academic Journal
Accession number :
18003072
Full Text :
https://doi.org/10.1109/IEMBS.2007.4353406