Development of a Computer Vision Framework for Improved Remotely Piloted Aircraft Operations

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Creator: 

Ooi, Brendan Xin Zhi

Date: 

2020

Abstract: 

This thesis proposes a computer vision framework to enable improved operations of Remotely Piloted Aircraft equipped with onboard image sensors. The main use of payload image sensors is to provide visual imagery data to the system for real-time or post-processing applications; the application of an image quality metric and the ground sampling distance of the image sensor can be used to predict the performance of an image sensor in enabling the image classification task. This information is used to determine the mission-specific operational envelope of the aircraft, to ensure that visual data quality requirements are met. The application of a convolutional neural network for image processing is also presented. Finally, a vision-based positioning system is developed, and it achieves an average position estimation difference of 17.87 cm compared to a commercially available indoor localization system; this system provides a position update rate of 11.48 Hz.

Subject: 

Engineering - Aerospace
Artificial Intelligence
Robotics

Language: 

English

Publisher: 

Carleton University

Thesis Degree Name: 

Master of Applied Science: 
M.App.Sc.

Thesis Degree Level: 

Master's

Thesis Degree Discipline: 

Engineering, Aerospace

Parent Collection: 

Theses and Dissertations

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