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Carnegie Mellon Robotics Institute

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Abstract

We present a robust method for detecting and recognizing topological features in underground mines. Our method involves performing Delaunay triangulations on range scans to extract points of interest, such as intersecting corridors. By combining these interest points into a topological map, we have a valuable tool for navigation and localization in large scale, highly cyclic environments. We present results from a research coal mine near Pittsburgh, PA.

Notes

Associated Project(s): 3D Mine Mapping

Number of pages: 7

Text Reference

David Silver, David Ferguson, Aaron Christopher Morris, and Scott Thayer, "Feature Extraction for Topological Mine Maps," Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), September, 2004, pp. 773 - 779.

BibTeX Reference

@inproceedings{Silver_2004_4730,
   author = "David Silver and David Ferguson and Aaron Christopher Morris and Scott Thayer",
   title = "Feature Extraction for Topological Mine Maps",
   booktitle = "Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS)",
   pages = "773 - 779",
   month = "September",
   year = "2004",
   volume = "1",
}

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