| Art der Veröffentlichung: |
Artikel in Konferenzband |
| Autor: |
Armin Burchardt, Tim Laue, Thomas Röfer |
| Herausgeber: |
Javier Ruiz-del-Solar, Eric Chown, Paul G. Plöger |
| Titel: |
Optimizing Particle Filter Parameters for Self-Localization |
| Buch / Sammlungs-Titel: |
RoboCup 2010: Robot Soccer World Cup XIV |
| Seite(n): |
145 – 156 |
| Serie / Reihe: |
Lecture Notes in Artificial Intelligence |
| Erscheinungsjahr: |
2011 |
| Verleger: |
Springer, Heidelberg |
| Abstract / Kurzbeschreibung: |
Particle filter-based approaches have proven to be capable of efficiently solving the self-localization problem in RoboCup scenarios and are therefore applied by many participating teams. Nevertheless, they require a proper parametrization - for sensor models and dynamic models as well as for the configuration of the algorithm - to operate reliably. In this paper, we present an approach for optimizing all relevant parameters by using the Particle Swarm Optimization algorithm. The approach has been applied to the self-localization component of a Standard Platform League team and shown to be capable of finding a parameter set that leads to more precise position estimates than the previously used hand-tuned parametrization. |
| PDF Version: |
http://www.informatik.uni-bremen.de/kogrob/papers/RC-Burchardt-etal-11.pdf |
| Status: |
Reviewed |
| Letzte Aktualisierung: |
06. 11. 2013 |
