Title page for ETD etd-05032012-104351


Type of Document Master's Thesis
Author Torok, Matthew M.
Author's Email Address mtorok@vt.edu
URN etd-05032012-104351
Title Autonomous Sample Collection Using Image-Based 3D Reconstructions
Degree Master of Science
Department Mechanical Engineering
Advisory Committee
Advisor Name Title
Golparvar-Fard, Mani Committee Co-Chair
Kochersberger, Kevin Bruce Committee Co-Chair
Sandu, Corina Committee Member
Keywords
  • Building Crack Detection
  • Autonomous Sample Collection
  • Image-based 3D Reconstruction
  • Scoops
  • Robotics
Date of Defense 2012-04-26
Availability unrestricted
Abstract
Sample collection is a common task for mobile robots and there are a variety of manipulators

available to perform this operation. This thesis presents a novel scoop sample collection

system design which is able to both collect and contain a sample using the same hardware.

To ease the operator burden during sampling the scoop system is paired with new

semi-autonomous and fully autonomous collection techniques. These are derived from data

provided by colored 3D point clouds produced via image-based 3D reconstructions. A custom

robotic mobility platform, the Scoopbot, is introduced to perform completely automated

imaging of the sampling area and also to pick up the desired sample. The Scoopbot is wirelessly

controlled by a base station computer which runs software to create and analyze the

3D point cloud models. Relevant sample parameters, such as dimensions and volume, are

calculated from the reconstruction and reported to the operator. During tests of the system

in full (48 images) and fast (6-8 images) modes the Scoopbot was able to identify and

retrieve a sample without any human intervention. Finally, a new building crack detection

algorithm (CDA) is created to use the 3D point cloud outputs from image sets gathered by

a mobile robot. The CDA was shown to successfully identify and color-code several cracks

in a full-scale concrete building element.

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