Princeton University Library Catalog

Particle Filter Localization for Unmanned Aerial Vehicles Using Augmented Reality Tags

Author/​Artist:
Kelley, Edward [Browse]
Format:
Senior thesis
Language:
English
Advisor(s):
Rusinkiewicz, Szymon [Browse]
Department:
Princeton University. Department of Computer Science [Browse]
Class year:
2013
Description:
58 pages
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.