Does JoiTech Messi dream of RoboCup Goal?

We focus on two critical features in big size robot soccer. First, efficient training is one of the important issues for RoboCup teams to adapt their robots on site. Real robot’s training takes time and may damage the hardware while simulated one may miss the important factors to be improved. Second, to predict behavior of opponent robots is necessary for big size robots because they cannot move quickly so far. To overcome the issues we developed a versatile simulator and a smart strategy to improve accuracy of shoot and block. The former consists of multiple channels of inputs such as a real live video image stream, a real but already recorded one, and virtual one. The two kinds of outputs are real robot motor commands and virtual ones. We can have any combination of input/output to reduce the amount of training (less damage to real robot hardware) while improving the robot behavior. The latter, a strategy, consists of opponent recognition and adaptive action planning. The opponent (goalie or shooter) is detected by simple background subtraction, and its behavior is predicted based on the velocity in the image. This enables a shooter to find the space to shoot a ball, and for a goalie to block the goal from the opponent player’s shooting. We successfully applied the system to the RoboCup 2013 humanoid league adult size, and got the championship as well as the best humanoid award (”Louis Vuitton Cup”).