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_MMAR_2021__A_simple_vision_based_navigation_and_control_strategy_for_autonomous_drone_racing(1).pdf (3.14 MB)
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A simple vision-based navigation and control strategy for autonomous drone racing

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posted on 22.04.2021, 09:04 by Artur Cyba, Hubert Szolc, Tomasz KryjakTomasz Kryjak
In this paper, we present a control system that allows a drone to fly autonomously through a series of gates marked with ArUco tags. A simple and low-cost DJI Tello EDU quad-rotor platform was used. Based on the API provided by the manufacturer, we have created a Python application that enables the communication with the drone over WiFi, realises drone positioning based on visual feedback, and generates control. Two control strategies were proposed, compared, and critically analysed. In addition, the accuracy of the positioning method used was measured.
The application was evaluated on a laptop computer (about 40 fps) and a Nvidia Jetson TX2 embedded GPU platform (about 25 fps). We provide the developed code on GitHub.

Funding

AGH University of Science and Technology project no. 16.16.120.773

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Email Address of Submitting Author

tomasz.kryjak@agh.edu.pl

ORCID of Submitting Author

0000-0001-6798-4444

Submitting Author's Institution

AGH University of Science and Technology

Submitting Author's Country

Poland

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