Title page for ETD etd-05062008-112710

Type of Document Master's Thesis
Author Sharkasi, Adam Tawfik
Author's Email Address sharkasi@vt.edu
URN etd-05062008-112710
Title Stereo Vision Based Aerial Mapping Using GPS and Inertial Sensors
Degree Master of Science
Department Mechanical Engineering
Advisory Committee
Advisor Name Title
Kochersberger, Kevin Bruce Committee Chair
Rhody, Harvey Committee Member
Wicks, Alfred L. Committee Member
  • Stereo Vision
  • Unmanned Systems
  • GPS
  • 3D Mapping
  • Inertial Measurement
Date of Defense 2008-04-30
Availability unrestricted
The robotics field has grown in recent years to a point where unmanned systems are no

longer limited by their capabilities. As such, the mission profiles for unmanned systems

are becoming more and more complicated, and a demand has risen for the deployment of

unmanned systems into the most complex of environments. Additionally, the objectives

for unmanned systems are once more complicated by the necessity for beyond line of

sight teleoperation, and in some cases complete vehicle autonomy.

Such systems require adequate sensory devices for appropriate situational awareness.

Additionally, a large majority of what is currently being done with unmanned systems

requires visual data acquisition. A stereo vision system is ideal for such missions as it

doubles as both an image acquisition device, and a range finding device. The 2D images

captured with a stereo vision system can be mapped to three dimensional point clouds

with reference to the optic center of one of the stereo cameras. While stand alone

commercial stereo vision systems are capable of doing just that, the GPS/INS aided

stereo vision system also has integrated 3-axis accelerometers, 3-axis gyros, 3-axis

magnetometer, and GPS receiver allowing for the measurement of the system’s position

and orientation in global coordinates. This capability provides the potential to georeference

the 3D data captured with the stereo camera.

The GPS/INS aided stereo vision system integrates a combination of commercial and inhouse

developed devices. The total system includes a Point Grey Research Bumblebee

stereovision camera, a Versalogic PC104 computer, a PCB designed for sensor

acquisition and power considerations, and a self contained battery. The entire system is

all contained within a 9.5” x 5” x 6.5” aluminum enclosure and weighs approximately 6

lbs. The system is also accompanied with a graphical user interface which displays the

geo-referenced data within a 3D virtual environment providing adequate sensor feedback

for a teleoperated unmanned vehicle.

This thesis details the design and implementation of the hardware and software included

within this system as well as the results of operation.

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