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Incremental supervised learning for mobile robot reactive control

โœ Scribed by Patrick Reignier; Volker Hansen; James L. Crowley

Publisher
Elsevier Science
Year
1997
Tongue
English
Weight
793 KB
Volume
19
Category
Article
ISSN
0921-8890

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โœฆ Synopsis

Reactive control for a mobile robot can be defined as a mapping from a perceptual space to a command space. This mapping can be hard-coded by fine user (potential fields, fuzzy logic), and can also be learnt. This paper is concerned with supervised learning for perception to action mapping for a mobile robot. Among the existing neural approaches for supervised learning of a function, we have selected the grow and learn network for its properties adapted to robotic problems: incrementality and flexible structure. We will present the results we have obtained with this network using first raw sensor data and then pre-processed measures with the automatic construction of virtual sensors.

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