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Probabilistic Framework for Sensor Management

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Book Series: Karlsruhe Series on Intelligent Sensor-Actuator-Systems / Universität Karlsruhe, Intelligent Sensor-Actuator-Systems Laboratory ISSN: 18673813 ISBN: 9783866444058 Year: Volume: 7 Pages: VI, 159 p. DOI: 10.5445/KSP/1000012224 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Computer Science
Added to DOAB on : 2019-07-30 19:59:17
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A probabilistic sensor management framework is introduced, which maximizes the utility of sensor systems with many different sensing modalities by dynamically configuring the sensor system in the most beneficial way. For this purpose, techniques from stochastic control and Bayesian estimation are combined such that long-term effects of possible sensor configurations and stochastic uncertainties resulting from noisy measurements can be incorporated into the sensor management decisions.

Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications

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Book Series: Karlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe ISSN: 18636489 ISBN: 9783731503385 Year: Volume: 19 Pages: V, 270 p. DOI: 10.5445/KSP/1000045491 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Computer Science
Added to DOAB on : 2019-07-30 20:01:58
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By restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed into an algebraically simple form, which allows for computationally efficient algorithms. Three problem settings are discussed in this thesis: (1) filtering with Gaussians only, (2) Gaussian mixture filtering for strong nonlinearities, (3) Gaussian process filtering for purely data-driven scenarios. For each setting, efficient algorithms are derived and applied to real-world problems.

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