This document describes the RoboCup Humanoid League TeenSize team NimbRo Albert-Ludwigs-University Freiburg, Germany, as required by the qualification procedure for the competition to be held in Bremen in June 2006. Our team uses self-constructed robots for playing soccer. The paper describes the mechanical and electrical design of the robots. It also covers the software used for perception, be...

Humanoid soccer robots perceive their environment exclusively through cameras. This paper presents a monocular vision system that was originally developed for use in the RoboCup Humanoid League, but is expected to be transferable to other soccer leagues. Recent changes in the Humanoid League rules resulted in a soccer environment with less color coding than in previous years, which makes percep...

This paper describes the design and implementation of a 4 player RoboCup Simulation 2D team, which was build by adding Heuristic Accelerated Reinforcement Learning capabilities to basic players of the well-known UvA Trilearn team. The implemented agents learn by using a recently proposed Heuristic Reinforcement Learning algorithm, the Heuristically Accelerated Q–Learning (HAQL), which allows th...

FC Portugal 3D team is built upon the structure of our previous Simulation league 3D teams and standard platform league team. Our research on high-level soccer coordination methodologies and team plying is mainly focused on the adaptation of previously developed methodologies from our 2D soccer teams [1, 2, 3, 4, 5] to the 3D humanoid environment and on creating new coordination methodologies b...

This paper details the hardware, software and electrical design of our new humanoid platform for the adult size league at RoboCup 2014 to be held later this year in João Pessoa, Brazil. THORwIn is a 49Kg bipedal robot that will show our experience from previous RoboCup encounters with Humanoid platforms like DARwIn-OP, CHARLI, and XOS in robot soccer autonomy since RoboCup 2007 [1,2].

This paper describes the design and implementation of robotic agents for the RoboCup Simulation 2D category that learns using a recently proposed Heuristic Reinforcement Learning algorithm, the Heuristically Accelerated Q–Learning (HAQL). This algorithm allows the use of heuristics to speed up the well-known Reinforcement Learning algorithm Q–Learning. A heuristic function that influences the c...

How to improve the performance of a simulated soccer team using final game statistics? This is the question this research aims to answer using modelbased collaborative techniques and a robotic team – FC Portugal – as a case study. After developing a framework capable of automatically calculating the final game statistics through the RoboCup log files, a feature selection algorithm was used to s...

In the team described in this paper we realize a direct approach to soccer agents for the simulation league of the RoboCup '98-tournament. Its backbone is formed by a detailed world model. Based on information which is reconstructed on the world model level, the rule-based decision levels chose a relevant action. The architecture for the goalie is diierent from the regular players, introducing ...

This document describes the RoboCup Humanoid League team NimbRo of University of Freiburg in preparation for the competition to be held in Osaka in July 2005. Our team uses a variety of robots for playing soccer: RoboSapien, Kondo, Toni, and Fritz. These robots are either constructed in our lab, based on a construction kit, or based on a low-cost commercial robot. The paper describes the robot ...