Autonomous quadrotor unmanned aerial vehicle for culvert inspection
Name
766546246-MIT.pdf
Description
Full printable version
Size
4.04 MB
Format
Adobe PDF
Checksum (MD5)
e6c8e2221a6f6079865564b52d80b526
Author(s)
Serrano, Nathan E
Advisor(s)
Seth Teller, Nicholas Roy and Jonathan Williams.
Date Issued
2011
Publisher
Massachusetts Institute of Technology
Abstract
This document presents work done to lay the foundation for an Unmanned Aerial Vehicle (UAV) system for inspecting culverts. By expanding upon prior progress creating an autonomous indoor quadrotor, many basic hardware and software issues are solved. The main new functionality needed for the culvert inspection task was to utilize the Global Positioning System (GPS) available outdoors to make up for the relative scarcity of objects visible to the Light Detection And Ranging sensor (LIDAR). The GPS data is fused in a new state estimator, which also incorporates data from the scan matcher running on the LIDAR data, as well as the data from the quadrotor's Inertial Measurement Unit (IMU). This data is combined into a single estimate of the current state (position, orientation, velocity, angular velocity, and acceleration) of the quadrotor by an Extended Kalman Filter (EKF). This new state estimate enables autonomous outdoor navigation and operation of this micro-UAV.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 69).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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reproduction or distribution in any format is prohibited without written
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