Novelty Detection on a Mobile Robot Using Habituation
<|reference_start|>Novelty Detection on a Mobile Robot Using Habituation: 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.<|reference_end|>
@article{marsland2000novelty,
    title={Novelty Detection on a Mobile Robot Using Habituation},
    author={Stephen Marsland, Ulrich Nehmzow and Jonathan Shapiro},
    journal={arXiv preprint arXiv:cs/0006007},
    year={2000},
    archivePrefix={arXiv},
    eprint={cs/0006007},
    primaryClass={cs.RO cs.NE nlin.AO}
}