Title :
UAV-Borne 3-D Mapping System by Multisensor Integration
Author :
Nagai, Masahiko ; Chen, Tianen ; Shibasaki, Ryosuke ; Kumagai, Hideo ; Ahmed, Afzal
Author_Institution :
Earth Obs. Data Integration & Fusion Res. Initiative, Univ. of Tokyo, Tokyo
fDate :
3/1/2009 12:00:00 AM
Abstract :
To represent 3-D space in detail, it is necessary to acquire 3-D shapes and textures simultaneously and efficiently through the use of precise trajectories of sensors. However, there is no reliable, quick, cheap, and handy method for acquiring accurate high-resolution 3-D data on objects in outdoor and moving environments. In this paper, we propose a combination of charge-coupled device cameras, a small and inexpensive laser scanner, an inexpensive inertial measurement unit, and Global Positioning System for a UAV-borne 3-D mapping system. Direct georeferencing is achieved automatically using all of the sensors without any ground control points. A new method of direct georeferencing by the combination of bundle block adjustment and Kalman filtering is proposed. This allows objects to be rendered richly in shape and detailed texture automatically via a UAV from low altitude. This mapping system has been experimentally used in recovery efforts after natural disasters such as landslides, as well as in applications such as river monitoring.
Keywords :
CCD image sensors; Global Positioning System; Kalman filters; geophysical signal processing; image processing; infrared imaging; motion compensation; photogrammetry; position measurement; remotely operated vehicles; sensor fusion; terrain mapping; Global Positioning System; Kalman filtering; UAV borne 3D mapping system; automatic direct georeferencing; bundle block adjustment; charge coupled device cameras; high resolution 3D data acquisition; inertial measurement unit; laser scanner; low altitude UAV; moving environments; multisensor integration; outdoor environments; precise sensor trajectory; simultaneous 3D shape-texture acquisition; unmanned aerial vehicle; Image orientation analysis; Kalman filtering; image sensors; inertial navigation; lasers; multisensor systems;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2008.2010314