UAV-Based Stereo Vision for Rapid Aerial Terrain Mapping

摘要

Aerial terrain mapping has been used for many years to monitor natural habitats and ecosystems, assist in urban planning, and monitor trends in land usage. Recent improvements in digital imaging, LiDAR, and synthetic aperture radar have facilitated the generation of 3-D terrain models for analysis in these applications. Unfortunately, these systems typically require large manned aircraft and significant post-processing of data before viewable results are produced. This inhibits use of these technologies in time-critical applications such as disaster relief, autonomous obstacle avoidance, and landing-zone assessment for a vertical take-off and landing aircraft. This paper describes a wide-baseline stereo vision system that enables near-real-time generation of dense 3-D terrain maps. The key advantage of computational stereo vision over monocular structure-from-motion is that terrain can be reconstructed from a single synchronized pair of calibrated images. The paper describes a working prototype, and presents a novel approach for combining separate stereo maps into larger terrain mosaics. The new stereo system and algorithm have an accuracy ranging from 56 cm to 65 cm across the field of view at an altitude of 40 m. Also, dense correlation of the imagery generates over 2200 points/m2. The system weighs just 3.1 kg, roughly one-fourth the weight of comparable high-altitude mapping systems, at ca. one-tenth the cost. The paper also describes potential implementations using Field-Programmable Gate Arrays (FPGAs) and Application-Specific Integrated Circuits (ASICs) for real-time operation.