Using an object tracking algorithm by video image for the implementation of an autonomous target tracking function for UAV

Authors

DOI:

https://doi.org/10.18372/2073-4751.78.18956

Keywords:

UAV, OpenCV, pattern recognition, image recognition, tracker, autonomous management, single board computer

Abstract

The article examines the spheres of UAV commissioning. The problem of controlling the UAV by the operator through the control panel is described. The paper proposes an approach for implementing the autonomous function of following a given object. A software part consisting of a video stream processing module, object tracking, and control command generation was developed. The program additionally implements mechanisms to increase system reliability, such as data processing to prevent sudden movements and an algorithm to restore tracking when an object is lost. Further steps for the integration of the MAVLink library for the formation of control commands and the assembly of the hardware part of the system based on a Raspberry Pi single-board computer and a Pixhawk flight controller are described.

References

Dolintse B. I. Architecture of integrated navigation systems with enhanced coordi-nate accuracy and fault detection. Problems of Informatization and Management. 2023. Vol. 2, Iss. 74. P. 31–37. DOI: 10.18372/2073-4751.74.17878.

Zhukov I., Dolintse B., Balakin S. Enhancing Data Processing Methods to Im-prove UAV Positioning Accuracy. Interna-tional Journal of Image, Graphics and Sig-nal Processing. 2024. Vol. 16, Iss. 3. P. 100–110. DOI: 10.5815/ijigsp.2024.03.08.

Mohsan S. A. H. et al. Unmanned aerial vehicles (UAVs): practical aspects, applications, open challenges, security is-sues, and future trends. Intelligent Service Robotics. 2023. Vol. 16, Iss. 1. P. 109–137. DOI: 10.1007/s11370-022-00452-4.

Unmanned Aerial Vehicle - Glob-al Forecast. Markets and Markets. URL: https://www.marketsandmarkets.com/ResearchInsight/unmanned-aerial-vehicles-uav-market.asp (дата звернення: 25.06.2024).

Patil R. R. et al. Qualified scruti-ny for real-time object tracking framework. International Journal on Emerging Tech-nologies. 2020. Vol. 11 (3). P. 313–319.

Khan N. A. et al. Emerging use of UAV’s: secure communication protocol issues and challenges. Drones in Smart-Cities: Security and Performance. 2020. P. 37–55. DOI: 10.1016/B978-0-12-819972-5.00003-3.

Janku P. et al. Comparison of tracking algorithms implemented in OpenCV. 20th International Conference on Circuits, Systems, Communications and Computers. 2016. Vol. 76. 04031. DOI: 10.1051/matecconf/20167604031.

Hong T. et al. Real-Time Tracking Algorithm for Multi-Target UAV Based on Deep Learning. Remote Sensing. 2023. Vol. 15(1). 2. DOI: 10.3390/rs15010002.

Ortega L. D. et al. Low-Cost Computer-Vision-Based Embedded Systems for UAVs. Robotics. 2023. Vol. 12 (6). 145. DOI: 10.3390/robotics12060145.

Khan N. A. et al. A secure com-munication protocol for unmanned aerial vehicles. Computers, Materials and Contin-ua. 2021. Vol. 70(1), P. 601–618. DOI: 10.32604/cmc.2022.019419.

Published

2024-07-01

Issue

Section

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