Learning to Recognize Objects - Toward Automatic Calibration of Color Vision for Sony Robots

Color detection can be seriously affected by lighting conditions and other variations in the environment. The robot vision systems need to be recalibrated as lighting conditions change, otherwise they fail to recognize objects or classify them incorrectly. This paper describes experiments toward object recognition under different lightning conditions. We propose to train the vision system to recognize objects under different lightning conditions using machine learning. Learned knowledge is then used for object recognition. Having attached leaning module to the vision system facilitates the object recognition and provides conditions for automatic adaptation of the vision system to new environment.