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Proceedings Paper

Model Based Object Recognition Using LORD LTS-300 Touch Sensor
Author(s): J. W. Roach; P. K. Paripati; M. Wade
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Paper Abstract

This paper reports the result of a model driven touch sensor recognition experiment. The touch sensor employed is a large field tactile array. Object features appropriate for touch sensor recognition are extracted from a geometric model of an object, the dual spherical image. Both geometric and dynamic features are used to identify objects and their position and orientation on the touch sensor. Experiments show that geometric features extracted from the model are effective but that dynamic features must be determined empirically. Correct object identification rates even for very similar objects exceed ninety percent, a success rate much higher than we would have expected from only two-dimensional contact patterns. Position and orientation of objects once identified are very reliable. We conclude that large field tactile sensors could prove very useful in the automatic palletizing problem when object models (from a CAD system, for example) can be utilized.

Paper Details

Date Published: 29 March 1988
PDF: 5 pages
Proc. SPIE 0937, Applications of Artificial Intelligence VI, (29 March 1988); doi: 10.1117/12.946979
Show Author Affiliations
J. W. Roach, Virginia Tech (United States)
P. K. Paripati, Virginia Tech (United States)
M. Wade, Virginia Tech (United States)


Published in SPIE Proceedings Vol. 0937:
Applications of Artificial Intelligence VI
Mohan M. Trivedi, Editor(s)

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