Efficient and Reliable Sensor Models for Humanoid Soccer Robot Self-Localization
Tim Laue, Thijs Jeffry de Haas, Armin Burchardt, Colin Graf, Thomas Röfer, Alexander Härtl, Andrik Rieskamp
Editors: Changjiu Zhou, Enrico Pagello, Emanuele Menegatti, Sven Behnke, Thomas Röfer
In Proceedings of the Fourth Workshop on Humanoid Soccer Robots, (Humanoids-2009), 07.12.2009, Paris, 978-88-95872-03-2, 2009.
Although the precise structure of the color-coded environment as well as different well-proven state estimation algorithms are known, self-localization in a humanoid soccer robot scenario remains a challenging task. Different problems arise, e.g., from an inaccurate proprioception, the sparsity of unique features, or the perception of false positives. In this paper, we present approaches for reliable and efficient feature extraction together with the features' incorporation into a robust state estimation process.