Automatic White Line Recognition Method for Autonomous Soccer Robot

Abstract

In the RoboCup Middle Size League (MSL), self-localization based on white line information is crucial for the strategic plays of autonomous mobile robots. Conventionally, parameters for white line extraction were adjusted manually, leading to inconsistent accuracy depending on operator proficiency. To address this, we developed a system using deep learning to automatically recognize white lines with high precision from the robot’s onboard omnidirectional camera images. This method eliminates operator-dependency in parameter tuning and aims to achieve stable, highly accurate self-localization.