Paper
29 March 1988 Model Based Object Recognition Using LORD LTS-300 Touch Sensor
J. W. Roach, P. K. Paripati, M. Wade
Author Affiliations +
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.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
J. W. Roach, P. K. Paripati, and M. Wade "Model Based Object Recognition Using LORD LTS-300 Touch Sensor", Proc. SPIE 0937, Applications of Artificial Intelligence VI, (29 March 1988); https://doi.org/10.1117/12.946979
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KEYWORDS
Sensors

Spherical lenses

Image sensors

Object recognition

3D modeling

Data modeling

Image segmentation

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