Towards Eliminating Manual Color Calibration at RoboCup

Color calibration is a time-consuming, and therefore costly requirement for most robot teams at RoboCup. This paper presents an approach for autonomous color learning on-board a mobile robot with limited computational and memory resources. It works without any labeled training data and trains autonomously from a color-coded map of its environment. The process is fully implemented, completely autonomous, and provides high degree of segmentation accuracy. Most importantly, it dramatically reduces the time needed to train a color map in a new environment.

• Type: Conference
• Year: 2005
• Where: ROBOCUP
• Authors: Mohan Sridharan, Peter Stone
• Keywords: Autonomous Color, Color, Color Calibration, ROBOCUP 2005