Quinlan, Michael J. and Middleton, Richard H.
Multiple Model Kalman Filters: A Localization
Technique for RoboCup Soccer.
Lecture Notes in Computer Science (5949).
In the Standard Platform League (SPL) there are substantial sensor limitations due to the rapid motion of the camera, the limited field of view of the camera, and the limited number of unique landmarks.
These limitations place high demands on the performance and robustness of localization algorithms. Most of the localization algorithms implemented in RoboCup fall broadly into the class of particle based filters or
Kalman type filters including Extended and Unscented variants. Particle
Filters are explicitly multi-modal and therefore deal readily with ambiguous sensor data. In this paper, we discuss multiple-model Kalman filters
that also are explicitly multi-modal. Motivated by the RoboCup SPL,
we show how they can be used despite the highly multi-modal nature
of sensed data and give a brief comparison with a particle filter based
approach to localization.
||RoboCup 2009: Robot Soccer World Cup XIII Conference, Graz, Austria. 29 June - 5 July 2009. The original publication is available at www.springerlink.com
||Multiple Model Kalman Filters; Localization
Technique; RoboCup Soccer; particle filter;
||Science & Engineering > Hamilton Institute
||27 Apr 2011 14:58
|Journal or Publication Title:
||Lecture Notes in Computer Science
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