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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01z603qx549
Title: Particle Filter Localization for Unmanned Aerial Vehicles Using Augmented Reality Tags
Authors: Kelley, Edward
Advisors: Rusinkiewicz, Szymon
Department: Computer Science
Class Year: 2013
Abstract: 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.
Extent: 58 pages
URI: http://arks.princeton.edu/ark:/88435/dsp01z603qx549
Access Restrictions: Walk-in Access. This thesis can only be viewed on computer terminals at the Mudd Manuscript Library.
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Computer Science, 1988-2016

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