Local Movement Control with Neural Networks in the Small-Size League

Abstract. In the RoboCup small-size league, it is common to calculate the robot’s position calculated via a camera over the field as well as different kinds of artificial intelligence that’s run on a PC outside the field. In this case, the robot’s position must be predicted because of the various delays until the position data arrived at the robot. This paper focuses on the use of local sensors on the robot and a neural network to estimate the robot’s actual position. This paper shows how local sensors can compensate for the effect of latency times and how robot’s actual position can ascertained. Slip and friction effects that cannot be measured with local sensors are adjusted by a neutral network.