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Carnegie Mellon Robotics Institute

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Abstract

Describes a terrain mapping 3D vision system to build a high resolution terrain map from multiple range images and a digital elevation model (DEM). To build a composite map of the environment from multiple sensor data, the terrain mapping system needs a representation of the terrain that must be appropriate for multiple sensor data. Building a composite terrain map also requires estimating motion between sensor views and merging these views into a composite map. The terrain representation described consists of a grid-based representation, called elevation map. The authors develop the locus method to build elevation maps from range images. The locus method uses a model of the sensor to interpolate at arbitrary resolution without making any assumptions on the terrain shape other than the continuity of the surface. They also present a pixel-based or iconic terrain matching algorithm to estimate the vehicle motion from a sequence of range images. This terrain matching method uses the locus method to solve correspondence and occlusion problems. Comprehensive test results using a long sequence of range images and a DEM for rugged outdoor terrain are given.

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," Proceedings of the IEEE International Workshop on Intelligent Robots and Systems (IROS '90), 'Towards a New Frontier of Applications', July, 1990, pp. 127 - 134.

BibTeX Reference

@inproceedings{Kweon_1990_2439,
   author = "In So Kweon and Takeo Kanade",
   title = "High Resolution Terrain Map from Multiple Sensor Data",
   booktitle = "Proceedings of the IEEE International Workshop on Intelligent Robots and Systems (IROS '90), 'Towards a New Frontier of Applications'",
   pages = "127 - 134",
   month = "July",
   year = "1990",
   volume = "1",
}

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