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Adaptive Sampling with Mobile WSN: Simultaneous robot localisation and mapping of paramagnetic spatio-temporal fields
by Koushil Sreenath, Muhammad F. Mysorewala, Dan O. Popa and Frank L. Lewis
The Institution of Engineering and Technology, 2011
eISBN: 978-1-84919-258-3 | Cloth: 978-1-84919-257-6
Library of Congress Classification TK7872.D48A295 2011

ABOUT THIS BOOK | TOC
ABOUT THIS BOOK

Adaptive Sampling with Mobile WSN develops algorithms for optimal estimation of environmental parametric fields. With a single mobile sensor, several approaches are presented to solve the problem of where to sample next to maximally and simultaneously reduce uncertainty in the field estimate and uncertainty in the localisation of the mobile sensor while respecting the dynamics of the time-varying field and the mobile sensor. A case study of mapping a forest fire is presented. Multiple static and mobile sensors are considered next, and distributed algorithms for adaptive sampling are developed resulting in the Distributed Federated Kalman Filter. However, with multiple resources a possibility of deadlock arises and a matrix-based discrete-event controller is used to implement a deadlock avoidance policy. Deadlock prevention in the presence of shared and routing resources is also considered. Finally, a simultaneous and adaptive localisation strategy is developed to simultaneously localise static and mobile sensors in the WSN in an adaptive manner. Experimental validation of several of these algorithms is discussed throughout the book.

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