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Optimal Robot Self-Localization and Accuracy Bounds
Kenichi KANATANI Naoya OHTA
IEICE TRANSACTIONS on Information and Systems
Publication Date: 1999/02/25
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Processing,Computer Graphics and Pattern Recognition
mobile robot, image sensing, self-localization, statistical estimation, theoretical accuracy bound, bootstrap,
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We discuss optimal estimation of the current location of a mobile robot by matching an image of the scene taken by the robot with the model of the environment. We first present a theoretical accuracy bound and then give a method that attains that bound, which can be viewed as describing the probability distribution of the current location. Using real images, we demonstrate that our method is superior to the naive least-squares method. We also confirm the theoretical predictions of our theory by applying the bootstrap procedure.