The application of artificial neural networks to tactile robot visualization

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dc.contributor.advisor Coghill, George en
dc.contributor.advisor Tuck, David en
dc.contributor.author Ng, Edwin W. K. en
dc.date.accessioned 2020-07-08T04:58:32Z en
dc.date.available 2020-07-08T04:58:32Z en
dc.date.issued 1995 en
dc.identifier.uri http://hdl.handle.net/2292/52073 en
dc.description Full text is available to authenticated members of The University of Auckland only. en
dc.description.abstract Artificial Neural Network (ANN) computation is relatively new as an applications technology and is based on the paradigm of massively parallel distributed processing where the computation is performed over a large number of interconnected simple processing elements. The aim of this thesis is to apply ANN techniques to tactile robot visualisation which is the tactile sensing and perception of objects in a robot's workspace. The thesis is interdisciplinary in nature, combining topics from robotics, pattern recognition, ANNs and aspects of industrial engineering. The main focus is on robot trajectory planning, control of the tactile data acquisition process, and shape recognition, with an emphasis on providing a framework for the utilisation of inexpensive tactile sensors by industrial robots and the application of ANN techniques. Since every industrial process will have a different set of specifications, the development of the trajectory planning and shape recognition systems are addressed from a generalised point of view which may then be tailored for specific operational systems using the methodologies developed. A new angle-length perimeter (ALP) structural shape representation for tactile shape recognition was developed, implemented and tested within the prescribed framework. The ALP representation was shown to offer a consistent representation of two-dimensional polygonal shapes from highly variable tactile data. This enabled the modular ANN recognition systems that were developed to achieve good results. The general guidelines Iaid down in this thesis form a good basis for some general heuristic rules in the use of ANNs for solving complex problems, as well as a foundation for hardware implementation. en
dc.publisher ResearchSpace@Auckland en
dc.relation.ispartof PhD Thesis - University of Auckland en
dc.relation.isreferencedby UoA9974826414002091 en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. en
dc.rights Restricted Item. Full text is available to authenticated members of The University of Auckland only. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.title The application of artificial neural networks to tactile robot visualization en
dc.type Thesis en
thesis.degree.discipline Electrical and Electronic Engineering en
thesis.degree.grantor The University of Auckland en
thesis.degree.level Doctoral en
thesis.degree.name PhD en
dc.rights.holder Copyright: The author en


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