High Resolution Terrain Map from Multiple Sensor Data - Robotics Institute Carnegie Mellon University

High Resolution Terrain Map from Multiple Sensor Data

Workshop Paper, (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems, Vol. 1, pp. 127 - 134, July, 1990

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.

BibTeX

@workshop{Kweon-1990-13131,
author = {In So Kweon and Takeo Kanade},
title = {High Resolution Terrain Map from Multiple Sensor Data},
booktitle = {Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {1990},
month = {July},
volume = {1},
pages = {127 - 134},
}