Title: Stable encoding of robot paths using normalised radial basis networks: application to an autonomous wheelchair

Authors: Guido Bugmann, Paul Robinson, Kheng L. Koay

Addresses: School of Computing, Communications and Electronics, University of Plymouth, Plymouth PL4 8AA, UK. ' School of Computing, Communications and Electronics, University of Plymouth, Plymouth PL4 8AA, UK. ' School of Computing, Communications and Electronics, University of Plymouth, Plymouth PL4 8AA, UK

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.

Keywords: path following; path representation; RBF neural networks; robust control; sequence learning; autonomous wheelchair; robot navigation; collision avoidance; vehicle autonomous systems; autonomous vehicles; wheelchair control; robot control.

DOI: 10.1504/IJVAS.2006.012210

International Journal of Vehicle Autonomous Systems, 2006 Vol.4 No.2/3/4, pp.239 - 249

Available online: 28 Jan 2007 *

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