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Showing 1 to 3 of 3 for “"Bayes Filter"”.
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A COMPARISON OF THE PROBABILITY HYPOTHESIS DENSITY FILTER AND THE MULTIPLE HYPOTHESIS TRACKER FOR TRACKING TARGETS OF MULTIPLE TYPES
… target, and track objects of importance. The Bayes filter is the ideal algorithm for tracking a single target and there exists a significant body of work detailing tractable approximations of it with the notable examples of the Kalman and Extended Kalman filter. Multiple target tracking also …
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Probabilistic modeling of planar pushing
… problem of data-driven modeling and stochastic filtering of complex dynamical systems. The main contributions are GP-SUM, a filtering algorithm tailored to systems expressed as Gaussian processes (GP), and the probabilistic modeling of planar pushing by combining input-dependent GPs and GP-SUM. …
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Multirobot Tethering for Localization and Control
Particle filtering has proven to be an effective localization method for wheeled autonomous vehicles. For a given map, a sensor model, and observations, occasions arise where the vehicle could equally likely be in many locations of the map. Because particle filtering algorithms may generate low …