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Map-based multiple model tracking of a moving object (2004)
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| Venue: | Proceedings of eight RoboCup International Symposium |
| Citations: | 56 - 3 self |
BibTeX
@INPROCEEDINGS{Kwok04map-basedmultiple,
author = {Cody Kwok and Dieter Fox},
title = {Map-based multiple model tracking of a moving object},
booktitle = {Proceedings of eight RoboCup International Symposium},
year = {2004}
}
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Abstract
Abstract. In this paper we propose an approach for tracking a moving target using Rao-Blackwellised particle filters. Such filters represent posteriors over the target location by a mixture of Kalman filters, where each filter is conditioned on the discrete states of a particle filter. The discrete states represent the non-linear parts of the state estimation problem. In the context of target tracking, these are the non-linear motion of the observing platform and the different motion models for the target. Using this representation, we show how to reason about physical interactions between the observing platform and the tracked object, as well as between the tracked object and the environment. The approach is implemented on a four-legged AIBO robot and tested in the context of ball tracking in the RoboCup domain. 1
Keyphrases
map-based multiple model tracking discrete state tracked object target location physical interaction different motion model non-linear part ball tracking robocup domain four-legged aibo robot non-linear motion rao-blackwellised particle filter particle filter state estimation problem kalman filter target tracking
