Humanoid robots without internal sensors (e.g. compasses) tend to lose their orientation after a fall or collision. Furthermore, artificial environments are typically rotationally symmetric, causing ambiguities in self-localization. The approach proposed here does not alter the measurement step in the robot's self-localization. Instead it delivers confidence values for rotationally symmetric poses to the robot's behaviour controller, which then commands the robot's self-localization. The behaviour controller uses these confidence values and triggers commands to rearrange the self-localization's pose beliefs within one measurement cycle. This helps the self-localization algorithm to converge to the correct pose and prevents the algorithm from getting stuck in local minima. Experiments in a symmetric environment with a simulated and a real humanoid NAO robot show that this significantly improves the system. © 2014 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Bader, M., & Vincze, M. (2014). Spontaneous reorientation for self-localization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8371 LNAI, pp. 456–467). Springer Verlag. https://doi.org/10.1007/978-3-662-44468-9_40
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