- Kelley, Edward [Browse]
- Senior thesis
- 58 pages
- Rusinkiewicz, Szymon [Browse]
- Princeton University. Department of Computer Science [Browse]
- Class year
- Restrictions note
- Walk-in Access. This thesis can only be viewed on computer terminals at the Mudd Manuscript Library.
- Summary note
- This thesis proposes a system for capturing 3D models of large objects using autonomous
quadcopters. A major component of such a system is accurately localizing
the position and orientation, or pose, of the quadcopter in order to execute precise flight patterns. This thesis focuses on the design and implementation of a localization
algorithm that uses a particle filter to combine internal sensor measurements
and augmented reality tag detection in order to estimate the pose of an AR.Drone
quadcopter. This system is shown to perform significantly better than integrated
velocity measurements alone.