Creation of geo-referenced mosaics from MAV video and telemetry using constrained optimization and bundle adjustment

  • Authors:
  • Benjamin Heiner;Clark N. Taylor

  • Affiliations:
  • MAGICC Lab, Brigham Young University, Provo, UT;MAGICC Lab, Brigham Young University, Provo, UT

  • Venue:
  • IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
  • Year:
  • 2009

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Abstract

Miniature Aerial Vehicles (MAVs) are quickly gaining acceptance as a platform for performing remote sensing. However, because MAVs are flown close to the ground (300 meters or less in altitude), their field of view for any one image is relatively small. In addition, the context of the video (where and at what orientation are the objects being observed, the relationship between images) is unclear from any one image. To overcome these problems, we propose a geo-referenced mosaicing method that creates a mosaic from the captured images and geo-references the mosaic using information from the MAV IMU/GPS unit. Our method utilizes bundle adjustment within a constrained optimization framework. Using real MAV video, we have demonstrated our mosaic creation process on over 700 frames. Our method has been shown to produce the high quality mosaics to within 7m using tightly synchronized MAV telemetry data and to within 30m using only GPS information (i.e. no roll and pitch information).