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Highly efficient Localisation utilising Weightless neural systems

McElroy, Ben and Gillham, Michael and Howells, Gareth and Spurgeon, Sarah and Kelly, Stephen and Batchelor, John and Pepper, Matthew (2012) Highly efficient Localisation utilising Weightless neural systems. In: ESANN 2012 The 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - Proceedings. ESANN, pp. 543-548. ISBN 978-2-87419-049-0.

Abstract

Efficient localisation is a highly desirable property for an autonomous navigation system. Weightless neural networks offer a real-time approach to robotics applications by reducing hardware and software requirements for pattern recognition techniques. Such networks offer the potential for objects, structures, routes and locations to be easily identified and maps constructed from fused limited sensor data as information becomes available. We show that in the absence of concise and complex information, localisation can be obtained using simple algorithms from data with inherent uncertainties using a combination of Genetic Algorithm techniques applied to a Weightless Neural Architecture.

Item Type: Book section
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.P3 Pattern recognition systems
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: M. Gillham
Date Deposited: 01 Feb 2014 19:35 UTC
Last Modified: 14 Oct 2019 08:07 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/38134 (The current URI for this page, for reference purposes)
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