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.
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This work was partly supported by the National Nature Science Foundation under Grant 60775055 and 61074167.
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Feng, G., Liu, M. & Wang, G. Genetic algorithm based optimal placement of PIR sensors for human motion localization. Optim Eng 15, 643–656 (2014). https://doi.org/10.1007/s11081-012-9209-z
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DOI: https://doi.org/10.1007/s11081-012-9209-z