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By Year By Research Group | Random-Set-Based Estimation in Networked Environments and a Relationship to Kalman Filtering with Intermittent Observations Firstly, an exposition of random-set-based estimation in general networked control systems is examined. This provides a background for the work introduced in this paper. This exposition is also aimed at highlighting the advantages of the random-set-based ... A cornerstone for cognitive mobile agents is to represent the vast body of knowledge about space in which they operate. In order to be robust and efficient, such representation must address requirements imposed on the integrated system as a whole, but ... The problem of multi-object tracking with sen- sor networks is studied using the probability hypothesis density filter. The sensors are assumed to generate signals which are sent to an estimator via parallel channels which incur independent delays. These ... We re-examine the problem of global localization of a robot using a rigorous Bayesian framework based on the idea of random finite sets. Random sets allow us to naturally develop a complete model of the underlying problem accounting for the statistics of ... The problem of multiple-sensor-based multiple-object tracking is studied for adverse environments involving clutter (false positives), missing measurements (false negatives) and random target births and deaths (a priori unknown target numbers). Various (... |
