Cooperative sensing for 3D ball positioning in the RoboCup middle size league

As soccer in the RoboCup Middle Size League (MSL) starts resembling human soccer more and more, the time the ball is airborne increases. Robots equipped with a single catadioptric vision system will generally not be able to accurately observe depth due to limited resolution. Most teams, therefore, resort to projecting the ball on the field. Within the MSL several methods have already been explored to determine the 3D ball position, e.g., adding a high-resolution perspective camera or adding a Kinect sensor. This paper presents a new method which combines the omnivision camera data from multiple robots through triangulation. Three main challenges have been identified in designing this method: Inaccurate projections, Communication delay and Limited amount of data. An algorithm, considering these main challenges, has been implemented and tested. Performance tests with a non-moving ball (static situation) and two robots show an accuracy of 0.13 m for airborne balls. A dynamic test shows that a ball kicked by a robot could be tracked from the moment of the kick, if enough measurements have been received from two peer robots before the ball exceeds the height of the robots.