"The spatiotemporally varying network topology of mobile sensor networks makes it very suitable for applications such as reconstruction of environmental fields through sampling at locations that maximally reduce the largest uncertainty in the field estimate. Mobile sensor networks comprise of multiple heterogeneous resources and a deadlock-free resource scheduling in the presence of shared and routing resources becomes necessary to schedule the most efficient (cost/energy/time) resource for a task. Location information is imperative in sensor networks for most applications for localized sensing where localizing the network adaptively with no additional hardware is important. Adaptive sampling approaches for spatially distributed static linear and Gaussian fields with mobile robotic sensors are formulated and experimentally validated. Resource scheduling algorithms for dispatching resources in a deadlock-free manner in systems with shared and routing resources are mathematically formulated and experimentally validated. Simultaneous and Adaptive localization algorithms for sensor network localization through simple geometric constraints are validated through simulations. (Abstract shortened by UMI.)."
"The book is organized into three parts: preliminaries, single-robot adaptive sampling and multi-resource strategies."
"This book presents systematic methods for estimating environmental fields using multiple mobile sensors."
"This book presents systematic methods for estimating environmental fields using multiple mobile sensors."@en
"The book is organized into three parts: preliminaries, single-robot adaptive sampling and multi-resource strategies"
ProQuest Dissertations and Theses (Electronic resource collection)
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University of Texas at Arlington. College of Engineering.
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