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Optimization and Engineering
Erschienen in: Optimization and Engineering 3/2014

01.09.2014

Genetic algorithm based optimal placement of PIR sensors for human motion localization

verfasst von: Guodong Feng, Min Liu, Guoli Wang

Erschienen in: Optimization and Engineering | Ausgabe 3/2014

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Abstract

This paper studies the optimal placement of pyroelectric infrared (PIR) sensors in developing the infrared motion sensing system for human motion localization. In particular, we explore the use of genetic algorithm (GA) in optimizing both the deployment and the modulated field of view (FOV) of the PIR sensors for improving the localization performance. Two criteria, the average and maximum localization errors, are used to evaluate the localization performance. In addition, the numerical analysis is presented to offer a guidance on the searching spaces of the design parameters in implementing GA optimization. The proposed GA-based design approach is validated by means of both simulation and experimental studies in the context of human-following mobile robots.
Vorheriger Artikel A local approximation based multi-objective optimization algorithm with applications
Nächster Artikel Design of a decentralized framework for collaborative product design using memetic algorithms

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Metadaten
Titel
Genetic algorithm based optimal placement of PIR sensors for human motion localization
verfasst von
Guodong Feng
Min Liu
Guoli Wang
Publikationsdatum
01.09.2014
Verlag
Springer US
Erschienen in
Optimization and Engineering / Ausgabe 3/2014
Print ISSN: 1389-4420
Elektronische ISSN: 1573-2924
DOI
https://doi.org/10.1007/s11081-012-9209-z

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