Constraint Based Localization on a Humanoid Robot

In this paper we will present an application for constraint based methods to self localize within the RoboCup domain. During a robotic soccer game, robots of a team need to know where they and their team mates are on the field, therefore they need to localize themselves. For self localization, constraint based methods can be an effective alternative to classic Bayesian approaches as Kalman filters or Monte-Carlo methods. In this paper we will present, how constraint based techniques can be applied to a humanoid robot. Therefore we will implement constraint based methods in a humanoid robot ”NAO” and see how the constraint based approach works within the Standard Platform League.