Date of Publication
12-9-2019
Document Type
Master's Thesis
Degree Name
Master of Science in Mechanical Engineering
Subject Categories
Mechanical Engineering
College
Gokongwei College of Engineering
Department/Unit
Mechanical Engineering
Thesis Adviser
Alvin Chua
Abstract/Summary
Existing Unmanned Aerial Vehicles are typically controlled by the use of Radio Control which is a specialized device that translates button presses and joystick commands into movement. This means that control of an Unmanned Aerial Vehicle is both susceptible to radio interference, and is unintuitive. Recent research has proven that hand gestures are the most intuitive method for quadcopter control. However, past research has always used ground-based computers to perform gesture recognition algorithms, which means that the overall system is still susceptible to electromagnetic interference. This thesis presents the development of a quadrotor Unmanned Aerial Vehicle that uses an onboard companion computer to achieve gesture recognition with a deep learning algorithm without the need for a ground-based computer.
Abstract Format
html
Language
English
Format
Electronic
Accession Number
CDTG007413
Keywords
Drone aircraft—Control systems; Gesture recognition (Computer science)
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Recommended Citation
Ng, C. Y. (2019). Development of a UAV with hand gesture recognition using deep learning. Retrieved from https://animorepository.dlsu.edu.ph/etd_masteral/6393
Embargo Period
9-21-2022
