Stable encoding of robot paths using normalised radial basis networks: application to an autonomous wheelchair Online publication date: Sun, 28-Jan-2007
by Guido Bugmann, Paul Robinson, Kheng L. Koay
International Journal of Vehicle Autonomous Systems (IJVAS), Vol. 4, No. 2/3/4, 2006
Abstract: A Neural Network (NN) using Normalised Radial Basis Functions (NRBF) is used for encoding the sequence of positions forming the path of an autonomous wheelchair. The network operates by continuously producing the next position for the wheelchair. As the path passes several times over the same point, additional phase information is added to the position information. This avoids the aliasing problem. The use of normalised RBFs creates an attraction field over the whole space and enables the wheelchair to recover from perturbations, e.g. due to the avoidance of people.
Online publication date: Sun, 28-Jan-2007
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Vehicle Autonomous Systems (IJVAS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com