UNSCARF, A Color Vision System for the Detection of Unstructured Roads

J. Crisman and Chuck Thorpe
Proceedings of IEEE International Conference on Robotics and Automation, May, 1991, pp. 2496 - 2501.


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Abstract
The problem of navigating a robot vehicle on unstructured roads that have no lane markings, may have degraded surfaces and edges, and may be partially obscured by strong shadows is addressed. These conditions cause many road following systems to fail. The authors have build a system, UNSCARF, which is based on pattern recognition techniques, for successfully navigating on a variety of unstructured roads. UNSCARF does not need a road location prediction to find the location of the road; therefore, UNSCARF can be used as a bootstrapping system. It uses a clustering technique to group pixels with similar colors and locations. It then matches models of road shape to locate the roads in the image. These methods are more robust in noisy conditions than other road interpretation techniques. UNSCARF has been integrated into a navigation system that has successfully driven a test vehicle in may types of weather conditions.

Notes
Associated Center(s) / Consortia: Vision and Autonomous Systems Center
Associated Lab(s) / Group(s): NavLab

Text Reference
J. Crisman and Chuck Thorpe, "UNSCARF, A Color Vision System for the Detection of Unstructured Roads," Proceedings of IEEE International Conference on Robotics and Automation, May, 1991, pp. 2496 - 2501.

BibTeX Reference
@inproceedings{Thorpe_1991_1641,
   author = "J. Crisman and Chuck Thorpe",
   title = "UNSCARF, A Color Vision System for the Detection of Unstructured Roads",
   booktitle = "Proceedings of IEEE International Conference on Robotics and Automation",
   pages = "2496 - 2501",
   month = "May",
   year = "1991",
   volume = "3",
}