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Green Image
Issue No. 02 - February (1992 vol. 14)
ISSN: 0162-8828
pp: 278-292
ABSTRACT
<p>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.</p>
INDEX TERMS
3D vision; robot vision; computerised navigation; terrain map; multiple sensor data; locus method; sensor geometry; digital elevation map; synthetic range images; mobile robots; terrain models; computational geometry; computer vision; computerised navigation; computerised pattern recognition; mobile robots
CITATION
T. Kanade, I.S. Kweon, "High-Resolution Terrain Map from Multiple Sensor Data", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 14, no. , pp. 278-292, February 1992, doi:10.1109/34.121795
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