Efficient Sensor Placement Optimization Using Gradient Descent and Probabilistic Coverage

Autor: Vahab Akbarzadeh, Julien-Charles Lévesque, Christian Gagné, Marc Parizeau
Jazyk: angličtina
Rok vydání: 2014
Předmět:
Zdroj: Sensors, Vol 14, Iss 8, Pp 15525-15552 (2014)
Druh dokumentu: article
ISSN: 1424-8220
DOI: 10.3390/s140815525
Popis: We are proposing an adaptation of the gradient descent method to optimize the position and orientation of sensors for the sensor placement problem. The novelty of the proposed method lies in the combination of gradient descent optimization with a realistic model, which considers both the topography of the environment and a set of sensors with directional probabilistic sensing. The performance of this approach is compared with two other black box optimization methods over area coverage and processing time. Results show that our proposed method produces competitive results on smaller maps and superior results on larger maps, while requiring much less computation than the other optimization methods to which it has been compared.
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