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Carnegie Mellon Robotics Institute

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Abstract

We present techniques for building models of complex environments from range data gathered at multiple viewpoints. The challenges in this problem are: the matching of unregistered views without prior knowledge of pose, the use of very large data sets, and the manipulation of data sets of different resolutions and from different sensors. Our approach is unique in that no prior knowledge of the relative viewpoints is needed in order to register the data. We show results in building maps of interior environment from range finding data, building large terrain maps from ground-based and from aerial data, and from an operational for mapping from stereo data for hazardous environment characterization. The paper summarizes the major results obtained so far in this area.

Notes

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

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

Associated Project(s): Automatic 3D Modeling from Range Images

Text Reference

Daniel Huber, Owen Carmichael, and Martial Hebert, "3D map reconstruction from range data," Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '00), April, 2000, pp. 891 - 897.

BibTeX Reference

@inproceedings{Huber_2000_3556,
   author = "Daniel Huber and Owen Carmichael and Martial Hebert",
   title = "3D map reconstruction from range data",
   booktitle = "Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '00)",
   pages = "891 - 897",
   month = "April",
   year = "2000",
   volume = "1",
}

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