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		<rdfs:label>The Dynamic Sensor Coverage Problem</rdfs:label>
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		<property:Abstract rdf:datatype="http://www.w3.org/2001/XMLSchema#string">We introduce a theoretical framework for the dynamic sensor coverage
problem for a simple case with multiple discrete time linear dynamical systems
located in different spacial locations. The objective is to keep an appreciable
estimate of the states of the systems at all times by deploying a few mobile sensors.
The sensors are assumed to have a limited range and they implement a Kalman
filter to estimate the states of all the systems. The motion of the sensor is modeled
as a discrete time discrete state Markov chain. Based on some recent results on
the Kalman filtering problem with intermittent observations by Sinopoli et. al., we
derive conditions under which a single sensor fails to solve the coverage problem.
We also give conditions under which we can guarantee that a single sensor is
enough to solve the dynamic coverage problem.</property:Abstract>
		<property:Authors rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Abhishek Tiwari, Myungsoo Jun, David E. Jeffcoat, Richard M. Murray</property:Authors>
		<property:ID rdf:datatype="http://www.w3.org/2001/XMLSchema#string">2004w</property:ID>
		<property:Source rdf:datatype="http://www.w3.org/2001/XMLSchema#string">2005 IFAC World Congress</property:Source>
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		<property:Title rdf:resource="&wiki;The_Dynamic_Sensor_Coverage_Problem"/>
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