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Humanoid soccer robots perceive their environment exclusively throughcameras. This paper presents a monocular vision system that was originallydeveloped for use in the RoboCup Humanoid League, but is expected to betransferable to other soccer leagues. Recent changes in the Humanoid Leaguerules resulted in a soccer environment with less color coding than in previousyears, which makes perception of the game situation more challenging. Theproposed vision system addresses these challenges by using brightness andtexture for the detection of the required field features and objects. Oursystem is robust to changes in lighting conditions, and is designed forreal-time use on a humanoid soccer robot. This paper describes the maincomponents of the detection algorithms in use, and presents experimentalresults from the soccer field, using ROS and the igus Humanoid Open Platform asa testbed. The proposed vision system was used successfully at RoboCup 2015.

A Monocular Vision System for Playing Soccer in Low Color Information Environments