Computer vision is a broad and significant ongoing research challenge, even when performed on an individual image or on streaming video from a high-quality stationary camera with abundant computational resources. When faced with streaming video from a lower-quality, rapidly moving camera and limited computational resources, the challenge increases. We present our implementation of a vision system on a mobile robot platform that uses a camera image as the primary sensory input. Having to perform all processing, including segmentation and object detection, in real-time on-board the robot, eliminates the possibility of using some state-of-the-art methods that otherwise might apply. We describe the methods that we developed to achieve a practical vision system within these constraints. Our approach is fully implemented and tested on a team of Sony AIBO robots.

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In IEEE/RSJ International Conference on Intelligent Robots and Systems, August 2005.

@InProceedings{IROS2005-vision, title={Real-Time Vision on a Mobile Robot Platform}, author={Mohan Sridharan and Peter Stone}, booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems}, month={August}, url="http://www.cs.utexas.edu/users/ai-lab?IROS2005-vision", year={2005} }