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Real-time sensor data for efficient localisation employing a weightless neural system

McElroy, B; Gillham, M; Howells, G; Kelly, S; Spurgeon, S; Pepper, M; (2012) Real-time sensor data for efficient localisation employing a weightless neural system. In:

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Abstract

Mobile robotic localisation obtained from simple sensor data potentially offers real-time real-world integration. Computationally highly efficient Weightless Neural Networks, when used for location determination, further enhances performance potential. This paper introduces techniques for the identification of rooms or locations in the absence of complex and succinct information. Using simple floor colour and texture, and room geometrics from ranging data, although inherent uncertainties exist, these limited simple fused real-time sensor data can be easily resolved into a room identification criterion using architectures generated by a Genetic Algorithm technique applied to a Weightless Neural Network Architecture. © 2012 IEEE.

Type: Proceedings paper
Title: Real-time sensor data for efficient localisation employing a weightless neural system
ISBN-13: 9781467306720
DOI: 10.1109/IConSCS.2012.6502448
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: http://discovery.ucl.ac.uk/id/eprint/1515198
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