Artificial Intelligence-Based Human Gesture Tracking Control Techniques of Tello EDU Quadrotor Drone

Iskandar, M. and Bingi, K. and Rajanarayan Prusty, B. and Omar, M. and Ibrahim, R. (2023) Artificial Intelligence-Based Human Gesture Tracking Control Techniques of Tello EDU Quadrotor Drone. IET Conference Proceedings, 2023 (11). pp. 123-128. ISSN 27324494

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Abstract

This paper comprehensively reviews significant research on various artificial intelligence-based human gesture tracking techniques for the Tello EDU quadrotor drone. The gestures derived from image acquisition techniques include hand, eye, face, and body. Further, the methods include signal acquisition through leap motion and an electroencephalogram. The framework for developing the algorithm with various gestures is also demonstrated. The review table presents a thorough overview of the studies linked to the various human gesture-based techniques. It encompasses details such as the algorithm type, quantity of poses and landmarks, programming language, hardware and framework employed, and validation particulars. Furthermore, it comprehensively analyzes potential areas for future research and improvements within this field. © The Institution of Engineering & Technology 2023.

Item Type: Article
Additional Information: cited By 4; Conference of 2023 International Conference on Green Energy, Computing and Intelligent Technology, GEn-CITy 2023 ; Conference Date: 10 July 2023 Through 12 July 2023; Conference Code:195673
Uncontrolled Keywords: Aircraft detection; Artificial intelligence; Gesture recognition, Control techniques; Future improvements; Gesture tracking; Human gestures; Programming framework; Programming hardware; Quad rotors; Signal acquisitions; Tracking controls; Tracking techniques, Drones
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 04 Jun 2024 14:11
Last Modified: 04 Jun 2024 14:11
URI: https://khub.utp.edu.my/scholars/id/eprint/19010

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