In this paper, an efficient behavior for a humanoid soccer robot supporting a teammate manipulating the ball is proposed and evaluated. This approach has been derived from human soccer tactics, requires only minimal information about the current state of the game and is therefore well suited for robots with directed vision and limited motion abilities like humanoid robots. The position of the s...

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].

In this paper an evolutionary algorithm is developed to learn a fuzzy knowledge base for the control of a soccer playing micro-robot from any configuration belonging to a grid of initial configurations to hit the ball along the ball to goal line of sight. The knowledge base uses relative co-ordinate system including left and right wheel velocities of the robot. Final path positions allow forwar...

This paper provides a brief description of Robo-Erectus Senior (RESr) AdultSize soccer playing humanoid robot developed at Advanced Robotics and Intelligent Control Centre of Singapore Polytechnic. We are currently in the stage of building a new hardware for this year competition. The new robot, RESr Bv-MkI will be used as the platform for competing in RoboCup humanoid league, and for our ongoi...

The authors have applied reinforcement learning methods to real robot tasks in several aspects. We selected a skill of soccer as a task for a vision-based mobile robot. In this paper, we explain two of our method; (1)learning a shooting behavior, and (2)learning a shooting with avoiding an opponent. These behaviors were obtained by a robot in simulation and tested in a real environment in RoboC...

An essential capability of a soccer playing robot is to robustly and accurately estimate its pose on the field. Tracking the pose of a humanoid robot is, however, a complex problem. The main difficulties are that the robot has only a constrained field of view, which is additionally often affected by occlusions, that the roll angle of the camera changes continously and can only be roughly estima...

In this paper, we show how reinforcement learning can be applied to real robots to achieve optimal robot behavior. As example, we enable an autonomous soccer robot to learn intercepting a rolling ball. Main focus is on how to adapt the Q-learning algorithm to the needs of learning strategies for real robots and how to transfer strategies learned in simulation onto real robots.

This paper presents a real-time visual tracking system in the robot soccer domain. The details of the Essex Wizards robot football team and its control system are described. A real-time visual tracking algorithm has been developed. Some initial results of the image pre-processing and visual tracking algorithms in real environment setting are given to show the performance of the system.

In this paper, we report on the current developments of our Mirosot Robot Soccer team, the “Robocoasters”, in preparation for the FIRA Robot World Cup 2002 in Korea. We describe a number of unique enhancements to both the vision systems and the control system. Vision enhancements include a unique shape recognition system, expanded from recognition of three shapes to five shapes for the middle l...

Our research is concerned with making a dynamic, closed loop, stabilized kick for the Nao robot. The Nao is a humanoid robot made by Aldebaran Robotics. It is used in the Standard Platform League of the RoboCup, an organization which organizes football (soccer) competitions for autonomous robots. Kicking, of course, is an important part of football, and thus a good kick is vital to achieving go...