Search Results - "Gning, A."

Constraints propagation techniques on intervals for a guaranteed localization using redundant data by Gning, A., Bonnifait, Ph

“…In order to estimate continuously the dynamic location of a car, dead reckoning and absolute sensors are usually merged. The models used for this fusion are…”
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Analysis of the EPSRC Principles of Robotics in regard to key research topics by Gning, A., Davis, D. N., Cheng, Y., Robinson, P.

“…In this paper, we review the five rules published in EPSRC Principles of Robotics with a specific focus on future robotics research topics. It is demonstrated…”
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Bernoulli Particle/Box-Particle Filters for Detection and Tracking in the Presence of Triple Measurement Uncertainty by Gning, A., Ristic, B., Mihaylova, L.

“…This work presents sequential Bayesian detection and estimation methods for nonlinear dynamic stochastic systems using measurements affected by three sources…”
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Parallelized Particle and Gaussian Sum Particle Filters for Large-Scale Freeway Traffic Systems by Mihaylova, L., Hegyi, A., Gning, A., Boel, R. K.

“…Large-scale traffic systems require techniques that are able to 1) deal with high amounts of data and heterogenous data coming from different types of sensors,…”
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Box-particle intensity filter by Schikora, M, Gning, A, Mihaylova, L, Cremers, D, Koch, W, Streit, R

“…This paper develops a novel approach for multi-target tracking, called box-particle intensity filter (box-iFilter). The approach is able to cope with unknown…”
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Guaranteed dynamic localization using constraints propagation techniques on real intervals by Gning, A., Bonnifait, P.

“…In order to get continuous dynamic localization of a mobile robot, dead reckoning and absolute sensors are usually merged. The models used for this fusion are…”
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Interval Macroscopic Models for Traffic Networks by Gning, A, Mihaylova, L, Boel, R K

“…The development of real-time traffic models is of paramount importance for the purposes of optimizing traffic flow. Inspired by the compositional model (CM)…”
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Dynamic Vehicle Localization using Constraints Propagation Techniques on Intervals A comparison with Kalman Filtering by Gning, A., Bonnifait, P.

“…In order to implement a continuous and robust dynamic localization of a mobile robot, the fusion of dead reckoning and absolute sensors is often used…”
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Guaranteed dynamic localization using constraints satisfaction techniques reaching global consistency by Gning, A., Bonnifait, Ph

“…This article deals with data fusion using ensemblist tools in general, and constraints satisfaction techniques on real intervals, in particular. Indeed, such…”
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Extended object tracking with convolution particle filtering by Angelova, D., Mihaylova, L., Petrov, N., Gning, A.

“…This paper proposes a sequential Monte Carlo filter (particle filter) for state and parameter estimation of dynamic systems. It is applied to the problem of…”
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Adapting Particle Filter on Interval Data for Dynamic State Estimation by Abdallah, F., Gning, A., Bonnifait, P.

“…Over the last years, particle filters (PF) have attracted considerable attention in the field of nonlinear state estimation due to their relaxation of the…”
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Nonlinear filtering using measurements affected by stochastic, set-theoretic and association uncertainty by Ristic, B., Gning, A., Mihaylova, L.

“…The problem is sequential Bayesian detection and estimation of nonlinear dynamic stochastic systems using measurements affected by three sources of…”
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A novel Sequential Monte Carlo approach for extended object tracking based on border parameterisation by Petrov, N., Mihaylova, L., Gning, A., Angelova, D.

“…Extended objects are characterised with multiple measurements originated from different locations of the object surface. This paper presents a novel Sequential…”
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Mixture of uniform probability density functions for non linear state estimation using interval analysis by Gning, A, Mihaylova, L, Abdallah, F

“…In this work, a novel approach to nonlinear non-Gaussian state estimation problems is presented based on mixtures of uniform distributions with box supports…”
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Rectangular Extended Object Tracking with Box Particle Filter Using Dynamic Constraints by Petrov, N, Mihaylova, L, Gning, A

“…Extended objects generate multiple measurements and are characterised with their size or volume. They require methods able to deal with the data association…”
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A box particle filter for stochastic and set-theoretic measurements with association uncertainty by Gning, A., Ristic, B., Mihaylova, L.

“…This work develops a novel estimation approach for nonlinear dynamic stochastic systems by combining the sequential Monte Carlo method with interval analysis…”
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Box-particle PHD filter for multi-target tracking by Schikora, M., Gning, A., Mihaylova, L., Cremers, D., Koch, W.

“…This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able…”
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Box Particle Filtering for extended object tracking by Petrov, N., Gning, A., Mihaylova, L., Angelova, D.

“…This paper focuses on real-time tracking of an extended object in the presence of clutter. This task reduces to the estimation of the object kinematic state…”
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Group object structure and state estimation in the presence of measurement origin uncertainty by Mihaylova, L., Gning, A.

“…This paper proposes a technique for motion and group structure estimation of moving targets based on evolving graph networks in the presence of measurement…”
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Dynamic clustering and belief propagation for distributed inference in random sensor networks with deficient links by Gning, A., Mihaylova, L.

“…A fundamental issue in real-world monitoring network systems is the choice of sensors to track local events. Ideally, the sensors work together, in a…”
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