GA-model based robust scene recognition for indoor mobile robots traveling operations using raw-image

Recognition of a working environment is critical for an autonomous vehicle such as a mobile robot to confirm its possible intelligence. Therefore it is necessary to equip a recognition system with a sensor, which can get environmental information. As an effective sensor, a CCD camera is generally thought to be useful for all kinds of mobile robots. However, it is thought to be hard to use the CCD camera for visual feedback, which requires acquisition of the information in real-time. This research presents a corridor recognition method using unprocessed gray-scale images, termed here the raw-images, and a genetic algorithm (GA), without any image information conversion, so as to perform the recognition process in real-time. The robustness of the method against noises in the environment, and the effectiveness of the method for real-time recognition have been verified using real corridor images.