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Novelty Detection on a Mobile Robot Using Habituation

Stephen Marsland·Ulrich Nehmzow·Jonathan Shapiro
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Abstract

In 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.

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Stephen Marsland, Ulrich Nehmzow, Jonathan Shapiro. 2000-06-02. Novelty Detection on a Mobile Robot Using Habituation. https://arxiv.org/abs/cs/0006007

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