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High-Resolution Terrain Map from Multiple Sensor Data

In So Kweon and Takeo Kanade
IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 14, No. 2, February, 1992, pp. 278-292.


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Abstract
The authors present 3-D vision techniques for incrementally building an accurate 3-D representation of rugged terrain using multiple sensors. They have developed the locus method to model the rugged terrain. The locus method exploits sensor geometry to efficiently build a terrain representation from multiple sensor data. The locus method is used to estimate the vehicle position in the digital elevation map (DEM) by matching a sequence of range images with the DEM. Experimental results from large-scale real and synthetic terrains demonstrate the feasibility and power of the 3-D mapping techniques for rugged terrain. In real world experiments, a composite terrain map was built by merging 125 real range images. Using synthetic range images, a composite map of 150 m was produced from 159 images. With the proposed system, mobile robots operating in rugged environments can build accurate terrain models from multiple sensor data.

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

Text Reference
In So Kweon and Takeo Kanade, "High-Resolution Terrain Map from Multiple Sensor Data," IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 14, No. 2, February, 1992, pp. 278-292.

BibTeX Reference
@article{Kweon_1992_2514,
   author = "In So Kweon and Takeo Kanade",
   journal = "High-Resolution Terrain Map from Multiple Sensor Data",
   booktitle = "IEEE Trans. on Pattern Analysis and Machine Intelligence",
   pages = "278-292",
   month = "February",
   year = "1992",
   volume = "14",
   number = "1",
}

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