Vision-Based Localization in RoboCup Environments

Authors:
Stefan Enderle;Marcus Ritter;Dieter Fox;Stefan Sablatnög;Gerhard K. Kraetzschmar;Günther Palm
Affiliations:
-;-;-;-;-;-
Venue:
RoboCup 2000: Robot Soccer World Cup IV
Year:
2001

Citing 1
Cited 3

Monte Carlo localization: efficient position estimation for mobile robots

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A Novel Approach to Efficient Monte-Carlo Localization in RoboCup

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Abstract

Knowing its position in an environment is an essential capability for any useful mobile robot. Monte-Carlo Localization (MCL) has become a popular framework for solving the self-localization problem in mobile robots. The known methods exploit sensor data obtained from laser range finders or sonar rings to estimate robot positions and are quite reliable and robust against noise. An open question is whether comparable localization performance can be achieved using only camera images, especially if the camera images are used both for localization and object recognition. In this paper, we discuss the problems arising from these characteristics and show experimentally that MCL nevertheless works very well under these conditions.