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Carnegie Mellon Robotics Institute

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Abstract

Obstacle detection is a key component of autonomous systems. In particular, when dealing with large robots in unstructured environments, robust obstacle detection is vital. In this paper, we describe an obstacle detection methodology which combines two complimentary methods: adaptive color segmentation, and stereo-based color homography. This algorithm is particularly suited for environments in which the terrain is relatively flat and of roughly the same color. We will show results in applying this method to an autonomous outdoor robot.

Keywords

Obstacle Detection, Color

Notes

Associated Center(s) / Consortia: National Robotics Engineering Center

Associated Project(s): Golf Course Mowing

Text Reference

Parag Batavia and Sanjiv Singh, "Obstacle Detection Using Adaptive Color Segmentation and Color Stereo Homography," Proceedings of the IEEE International Conference on Robotics and Automation, May, 2001.

BibTeX Reference

@inproceedings{Batavia_2001_3508,
   author = "Parag Batavia and Sanjiv Singh",
   title = "Obstacle Detection Using Adaptive Color Segmentation and Color Stereo Homography",
   booktitle = "Proceedings of the IEEE International Conference on Robotics and Automation",
   publisher = "IEEE",
   month = "May",
   year = "2001",
}

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