Terrain data base generation for autonomous land vehicle navigation

Abstract

The Defense Advanced Research Projects Agency (DARPA) Strategic Computing Program is a large, multi-year effort focused on developing the next generation of computers and machine intelligence. Within this program the Autonomous Land Vehicle (ALV) Project calls for the development and demostration of increasingly sophisticated autonomous land navigation capabilities. As part of this effort, the U.S. Army Engineer Topographic Laboratories (USAETL) has the task of producing a high-resolution, high-accuracy, experimental digital terrain data base of a 12-km² test site. This data base will be used in conjunction with inertial navigation and computer vision systems for autonomous traversal by the vehicle. The data base consist of six overlays including landforms, soils, surface drainage, land cover, roads, and a high-density digital elevation model (DEM). ALV application of the terrain data base include route planning and a-priori information for machine vision.

Data compilation was performed on the Computer-Assisted Photo Interpretation Research (CAPIR) system at USAETL. CAPIR is an ongoing research effort which addresses the issues of digital terrain data extraction, storage, and exploitation. This paper willaddress data requirements and systems for building terrain dta bases in support of experimental autonomous land vehicle navigation.