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29 March 2024
 
  » arxiv » cs.RO/0006007

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Novelty Detection on a Mobile Robot Using Habituation
Stephen Marsland ; Ulrich Nehmzow ; Jonathan Shapiro ;
Date 2 Jun 2000
Subject Robotics; Neural and Evolutionary Computing; Adaptation and Self-Organizing Systems ACM-class: I.2.6 | cs.RO cs.NE nlin.AO
AbstractIn this paper a novelty filter is introduced which allows a robot operating in an un structured environment to produce a self-organised model of its surroundings and to detect deviations from the learned model. The environment is perceived using the rob ot’s 16 sonar sensors. The algorithm produces a novelty measure for each sensor scan relative to the model it has learned. This means that it highlights stimuli which h ave not been previously experienced. The novelty filter proposed uses a model of hab ituation. Habituation is a decrement in behavioural response when a stimulus is pre sented repeatedly. Robot experiments are presented which demonstrate the reliable o peration of the filter in a number of environments.
Source arXiv, cs.RO/0006007
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