Generation of a multi-resolution database for Large-Scale terrain data

Abstract

Robot technology that can work robustly even in unknown, time-varying extreme disaster environments is demanded. As such a tough robot technology, we focus on the unmanned aerial vehicle (UAV) that can perform information collection and work from the air. It is possible to efficiently grasp disaster circumstances by comparing acquired data from UAV with the terrain data acquired beforehand. Although the acquisition of the terrain data has become much easier by the development of laser scanners, dense point-clouds of a city, a prefecture or a region cannot be dealt with on a computer because of its limited memory size. In this paper, we propose a method to generate a multi-resolution database for large-scale terrain data by using quadtree-based multi-layers and compare image data acquired by a UAV with the database to acquire damage states suffering from the disaster by an earthquake.