University of Hertfordshire

By the same authors

Towards intrinsically learned skin models in robots

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Original languageEnglish
Title of host publicationProceedings of the 2nd International Symposium on New Frontiers in Human-Robot Interaction - A Symposium at the AISB 2010 Convention
Pages72-75
Number of pages4
Publication statusPublished - 1 Dec 2010
Event2nd International Symposium on New Frontiers in Human-Robot Interaction - A Symposium at the AISB 2010 Convention - Leicester, United Kingdom
Duration: 29 Mar 20101 Apr 2010

Publication series

NameProceedings of the 2nd International Symposium on New Frontiers in Human-Robot Interaction - A Symposium at the AISB 2010 Convention

Conference

Conference2nd International Symposium on New Frontiers in Human-Robot Interaction - A Symposium at the AISB 2010 Convention
CountryUnited Kingdom
CityLeicester
Period29/03/101/04/10

Abstract

We describe the use of information-theoretic principles following [4] for sensoritopic map construction on a simulated "skin". This research constitutes a first step in robot body model learning based on uninterpreted tactile sensors. Results are reasonable, although our findings identify a serious limitation in the information distance metric: the distance is analytically bounded by the number of bins used for discretisation, so that reconstructions tend to "spherise". Furthermore, the tactile modality is significantly sparser than the visual modality, which introduces further artefacts in the information distance, particularly under maximum entropy binning. We conclude that some method which allows sensoritopic reconstruction directly from mutual information would be preferable.

ID: 17567695