Platooning control of drones with real-time deep learning object detection. (1st February 2023)

• Record Type: Journal Article
• Authors: Dai, Xin; Nagahara, Masaaki
• Is Part Of: Advanced robotics. Volume 37:Number 3(2023)
• Page Start: 220
• Page End: 225
• Publication Date: 2023-02-01
• Subjects: Platooning -- drones -- multi-agent systems -- deep learning -- object detection; Robotics -- Periodicals; Robotics -- Japan -- Periodicals; Robotics; Japan; Periodicals; 629.89205
• DOI: 10.1080/01691864.2022.2119888
• Languages: English
• ISSNs: 0169-1864

Abstract

ABSTRACT: In this short paper, we study platooning control of drones using only the information from a camera attached to each drone. For this, we adopt real-time objection detection based on a deep learning model called YOLO (you only look once). The YOLO object detector continuously estimates the relative position of the drone in front, by which each drone is controlled by a PD (Proportional-Derivative) feedback controller for platooning. The effectiveness of the proposed system is shown by indoor experiments with three drones. GRAPHICAL ABSTRACT: UF0001