Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.236217
Title: A Bayesian approach to optimal sensor placement
Author: Cameron, Alexander John
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 1989
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Abstract:
By "intelligently" locating a sensor with respect to its environment it is possible to minimize the number of sensing operations required to perform many tasks. This is particularly important for sensing media which provide only "sparse" data, such as tactile sensors and sonar. In this thesis, a system is described which uses the principles of statistical decision theory to determine the optimal sensing locations to perform recognition and localization operations. The system uses a Bayesian approach to utilize any prior object information (including object models or previously-acquired sensory data) in choosing the sensing locations.
Supervisor: Durrant-Whyte, Hugh F. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.236217  DOI: Not available
Keywords: Optical fiber detectors
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