Active global localization for a mobile robot using multiple hypothesis tracking.

We present a probabilistic approach for mobile robot localization using an incomplete topological world model. The method, called the multi-hypothesis localization (MHL), uses multi-hypothesis Kalman filter based pose tracking combined with a probabilistic formulation of hypothesis correctness to ge...

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Bibliographic Details

Published in:	IEEE Transactions on robotics and automation 17, 5 (2001).
Main Author:	Jensfelt, P.
Format:	Article
Language:	English
Subjects:	Bayes method. Kalman filter. Computational complexity. Global localization. Mobile robot. Multiple hypothesis tracking. Pose tracking. Probability.