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As unmanned aerial vehicle (UAV) applications become more complex and versatile there is an increasing need to allow multiple UAVs to cooperate to solve problems which are beyond the capability of each individual UAV. To provide more complete and accurate information about the environment we present a DyKnow federation framework for information integration in multi-node networks of UAVs. A federation...
In this paper a new logical arbitration protocol for fusion of inconsistent information is designed. It defines a selection of models of a premise set in a multi-modal logic that uses the standard format of adaptive logics. The selected models are obtained by a counting procedure on the derivable data conflicting among the various sources. Peculiar of this approach is the definition of weights for...
In this paper, we establish a link between belief functions on real numbers and the maximal coherent sets obtained in the framework of possibilistic distributions. Having proposed an original disjunctive rule of combination in the framework of continuous belief functions, we demonstrate theoretically that maximal coherent sets can be viewed as a particular case in the framework of belief functions.
Target tracking algorithms operate in an environment of uncertain measurement origin. Targets are randomly detected, and clutter measurements from unwanted random scatterers are present. A vast majority of target tracking algorithms have been developed with the assumption of infinite sensor resolution, where a measurement can have only one source. This assumption is not valid for real sensors, such...
In this paper, we present an optimal local map registration algorithm for constructing global maps from local relative maps for wireless sensor network localization applications. In the algorithm, local maps are transformed into a global map using a set of affine transforms with each consisting of a rotation, a reflection and a translation for each individual local map. The optimal transform is found...
For estimation and fusion tasks it is inevitable to approximate a Gaussian mixture by one with fewer components to keep the complexity bounded. Appropriate approximations can be typically generated by exploiting the redundancy in the shape description of the original mixture. In contrast to the common approach of successively merging pairs of components to maintain a desired complexity, the novel...
Ontologies are being used increasingly in fusion applications, particularly for higher-level fusion, where data must often be understood relationally. This research presents a methodology for utilizing ontologies to enhance the process of graph matching in fusion applications, particularly those associated with soft data (e.g., linguistic data existing in things such as intelligence messages). This...
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