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Abstract

We discuss the problem of building large, high-resolution three-dimensional representations of unstructured terrain using terrestrial range sensors, which operate at the scale of meters to hundreds of meters. Issues specific to this sensing modality include widely varying resolution, absence of reliably detectable features, and very large data sets. We have developed a map building algorithm that registers and integrates sequences of range images, and we demonstrate its capabilities by building large terrain maps (260 x 166 meters) using ground-based and low-altitude terrestrial range sensors.

Keywords

3D modeling, terrain mapping, spin images, surface registration

Notes

Sponsor: NSF Grant IRI-9711853 and ONR Grant N00014-95-1-0591

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Associated Lab(s) / Group(s): 3D Computer Vision Group

Associated Project(s): 3D Terrain Mapping

Number of pages: 7

Text Reference

Daniel Huber and Martial Hebert, "A New Approach to 3-D Terrain Mapping," Proceedings of the 1999 IEEE/RSJ International Conference on Intelligent Robotics and Systems (IROS '99), October, 1999, pp. 1121-1127.

BibTeX Reference

@inproceedings{Huber_1999_3191,
   author = "Daniel Huber and Martial Hebert",
   title = "A New Approach to 3-D Terrain Mapping",
   booktitle = "Proceedings of the 1999 IEEE/RSJ International Conference on Intelligent Robotics and Systems (IROS '99)",
   pages = "1121-1127",
   publisher = "IEEE",
   month = "October",
   year = "1999",
}

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