In this paper, we propose a novel autonomous robot vision system that can recognize an environment by itself. The developed system has self-motivation to search an interesting region using human-like selective attention and novelty scene detection models, and memorize the relative location information for selected regions. The selective attention model consists of bottom-up saliency map and low level top-down attention model. The novelty detection model generates a scene novelty using the topology information and energy signature in the selective attention model. Experimental results show that the developed system successfully identify an environment as well as changing of environment in nature scene.