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Published on 8 November 2024
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Fang,K.;Huang,Q.;Hao,Y. (2024). Autonomous Cargo Grabbing System for Drones Using Cameras and ROS. Applied and Computational Engineering,98,85-94.
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Autonomous Cargo Grabbing System for Drones Using Cameras and ROS

Kangrui Fang *,1, Qigong Huang 2, Yilin Hao 3
  • 1 College of Mechanical and Electrical Engineering, Central South University, Changsha, China
  • 2 College of Mechanical and Electrical Engineering, Central South University, Changsha, China
  • 3 College of Mechanical and Electrical Engineering, Central South University, Changsha, China

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/98/20241092

Abstract

With the rapid development of low-altitude economy, the functional requirements for logistics UAVs are constantly improving. In this paper, an unmanned aerial vehicle system (UAV) is proposed to realize autonomous grasping of goods. First of all, a new type of grasping device is proposed, which can be easily mounted on the UAV. The camera image stream mounted on the UAV was obtained through camera calibration and corrected. Subsequently, the object recognition algorithm was used to process the image frames, successfully identify the goods to be captured, and calculate the position and direction relationship between the UAV and the target cargo. Next, the speed of the drone is adjusted by the PID controller to achieve a stable landing above the target cargo. Then, the drone is equipped with a robotic claw innovatively designed by our team to complete the gripping of the goods. Subsequently, the drone lifted off and began to deliver cargo. Throughout the grabbing process, a laptop equipped with Ubuntu and ROS systems communicates with the drone via Wi-Fi. The feasibility of the whole system was proved by experiments.

Keywords

logistics drone, autonomous gripping, PID controller, mechanical claw, position and direction relationship.

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Cite this article

Fang,K.;Huang,Q.;Hao,Y. (2024). Autonomous Cargo Grabbing System for Drones Using Cameras and ROS. Applied and Computational Engineering,98,85-94.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2nd International Conference on Functional Materials and Civil Engineering

Conference website: https://2024.conffmce.org/
ISBN:978-1-83558-681-5(Print) / 978-1-83558-682-2(Online)
Conference date: 23 August 2024
Editor:Ömer Burak İSTANBULLU, Alan Wang
Series: Applied and Computational Engineering
Volume number: Vol.98
ISSN:2755-2721(Print) / 2755-273X(Online)

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