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Modeling Observation Uncertainty for Soccer Playing Humanoid Robots

In recent years, humanoid robot soccer robots have shown increasingly robust and fast locomotion, making perception, world modeling and behavior control important. In this paper, we present the world modeling approach of the Darmstadt Dribblers humanoid robot team, which won the competitions in the RoboCup Humanoid KidSize League in 2009 and 2010. The paper focuses on modeling observation uncertainties originating from different contributing factors centrally in one module. This allows different state estimators to use this data in a consistent way, independently of the specific state estimation approach used.