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A Smart UAV Platform for Railroad Inspection
- Date Issued:
- 2019
- Abstract/Description:
- Using quadcopters for analysis of an environment has been an intriguing subject of study recently. The purpose of this work is to develop a fully autonomous UAV platform for Railroad inspection The dynamics of the quadrotor is derived using Euler's and Newton's laws and then linearized around the hover position. A PID controller is designed to control the states of the quadrotor in a manner to effectively follow a vision-based path, using the down facing camera on a Parrot Mambo quadrotor. Using computer vision the distance from the position of the quadrotor to the position of the center of the path was found. Using the yaw controller to minimize this distance was found to be an adequate method of vision-based path following, by keeping the area of interest in the field of view of the camera. The downfacing camera is also simultaneously observing the path to detect defects using machine learning. This technique was able to detect simulated defects on the path with around 90% accuracy.
Title: | A Smart UAV Platform for Railroad Inspection. |
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17 downloads |
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Name(s): |
Debevec, Ryan, Author Elgohary, Tarek, Committee Chair Xu, Yunjun, Committee CoChair Lin, Kuo-Chi, Committee Member University of Central Florida, Degree Grantor |
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Type of Resource: | text | |
Date Issued: | 2019 | |
Publisher: | University of Central Florida | |
Language(s): | English | |
Abstract/Description: | Using quadcopters for analysis of an environment has been an intriguing subject of study recently. The purpose of this work is to develop a fully autonomous UAV platform for Railroad inspection The dynamics of the quadrotor is derived using Euler's and Newton's laws and then linearized around the hover position. A PID controller is designed to control the states of the quadrotor in a manner to effectively follow a vision-based path, using the down facing camera on a Parrot Mambo quadrotor. Using computer vision the distance from the position of the quadrotor to the position of the center of the path was found. Using the yaw controller to minimize this distance was found to be an adequate method of vision-based path following, by keeping the area of interest in the field of view of the camera. The downfacing camera is also simultaneously observing the path to detect defects using machine learning. This technique was able to detect simulated defects on the path with around 90% accuracy. | |
Identifier: | CFE0007623 (IID), ucf:52555 (fedora) | |
Note(s): |
2019-08-01 M.S.A.E. Engineering and Computer Science, Mechanical and Aerospace Engineering Masters This record was generated from author submitted information. |
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Subject(s): | A Smart UAV Platform for Railroad Inspection | |
Persistent Link to This Record: | http://purl.flvc.org/ucf/fd/CFE0007623 | |
Restrictions on Access: | public 2019-08-15 | |
Host Institution: | UCF |