Distributed adaptive sampling using bounded-errors

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Distributed adaptive sampling using bounded-errors
—This paper presents a communication/coordination/ processing architecture for distributed adaptive observation of a spatial field using a fleet of autonomous mobile sensors. One of the key difficulties in this context is to design scalable algorithms for incremental fusion of information across platforms robust to what is known as the “rumor problem”. Incremental fusion is in general based on a Bayesian approach, and algorithms (e.g. the Covariance Intersection, CI) which propagate consistent characterizations of the estimation error under this challenging situation have been proposed. In this paper, we propose to base inter-sensor fusion on a deterministic approach which considers that bounds to the observation errors are known, wich is intrinsically robust to the rumor problem. We present the equations that enable the determination of the ellipsoidal domain of uncertainty that covers the intersection of the individual sets describing sensor’s uncertainty, and show that th...
Kévin Huguenin, Maria-João Rendas
Added 04 Jun 2010
Updated 04 Jun 2010
Type Conference
Year 2007
Authors Kévin Huguenin, Maria-João Rendas
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