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Obstacle Detection Using Adaptive Color Segmentation and Color Stereo Homography

Parag Batavia and Sanjiv Singh
Carnegie Mellon University, Proceedings of the IEEE International Conference on Robotics and Automation, May, 2001

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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.

BibTeX Reference
@conference{Batavia-2001-8208,
title = {Obstacle Detection Using Adaptive Color Segmentation and Color Stereo Homography},
author = {Parag Batavia and Sanjiv Singh},
booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation},
keyword = {Obstacle Detection, Color},
publisher = {IEEE},
school = {Robotics Institute , Carnegie Mellon University},
month = {May},
year = {2001},
address = {Pittsburgh, PA},
}
2017-09-13T10:45:47+00:00