High-resolution terrain map from multiple sensor data
Kweon, I.S.
Kanade, T.
Vision & Autonomous Syst. Center, Carnegie Mellon Univ., Pittsburgh, PA;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Feb 1992
Volume: 14,
Issue: 2
On page(s): 278-292
ISSN: 0162-8828
References Cited: 24
CODEN: ITPIDJ
INSPEC Accession Number: 4139391
Digital Object Identifier: 10.1109/34.121795
Current Version Published: 2002-08-06
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
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