Detection of Aerial Balls in Robotic Soccer Using a Mixture of Color and Depth Information

Abstract

Detection of aerial objects is a difficult problem to tackle given the dynamics and speed of a flying object. The problem is even more difficult when considering a noncontrolled environment, where the predominance of a given color is not guaranteed, and/or when the vision system is located on a moving platform. Taking as an example the game of robotic soccer promoted by the RoboCup Federation, most of the teams participating in the soccer competitions detect the objects in the environment using an omni directional camera. Omni directional vision systems only detect the ball when it is on the ground, and thus precise information on the ball position when in the air is lost. In this paper we present a novel approach for 3D ball detection in which we use the color information to identify ball candidates and the 3D data for filtering the relevant color information. The main advantage of our approach is the low processing time, being thus suitable for real-time applications. We present experimental results showing the effectiveness of the proposed algorithm. Moreover, this approach was already used in the last official RoboCup Middle Size League competition. The goalkeeper was able to move to a right position in order to defend a goal, in situations where the ball was flying towards the goal.