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Open Access

ARTICLE

Advanced Video Processing and Data Transmission Technology for Unmanned Ground Vehicles in the Internet of Battlefield Things (loBT)

Tai Liu1,2, Mao Ye2,*, Feng Wu3, Chao Zhu2, Bo Chen2, Guoyan Zhang1,*
1 School of Cyber Science and Technology, Shandong University, Qingdao, 266237, China
2 Wuhan Zhongyuan Communication Co., Ltd., China Electronics Corporation, Wuhan, 430205, China
3 System Engineering Institute, Academy of Military Sciences, Beijing, 100141, China
* Corresponding Author: Mao Ye. Email: email; Guoyan Zhang. Email: email
(This article belongs to the Special Issue: Smart Roads, Smarter Cars, Safety and Security: Evolution of Vehicular Ad Hoc Networks)

Computers, Materials & Continua https://doi.org/10.32604/cmc.2025.072692

Received 01 September 2025; Accepted 10 October 2025; Published online 05 November 2025

Abstract

With the continuous advancement of unmanned technology in various application domains, the development and deployment of blind-spot-free panoramic video systems have gained increasing importance. Such systems are particularly critical in battlefield environments, where advanced panoramic video processing and wireless communication technologies are essential to enable remote control and autonomous operation of unmanned ground vehicles (UGVs). However, conventional video surveillance systems suffer from several limitations, including limited field of view, high processing latency, low reliability, excessive resource consumption, and significant transmission delays. These shortcomings impede the widespread adoption of UGVs in battlefield settings. To overcome these challenges, this paper proposes a novel multi-channel video capture and stitching system designed for real-time video processing. The system integrates the Speeded-Up Robust Features (SURF) algorithm and the Fast Library for Approximate Nearest Neighbors (FLANN) algorithm to execute essential operations such as feature detection, descriptor computation, image matching, homography estimation, and seamless image fusion. The fused panoramic video is then encoded and assembled to produce a seamless output devoid of stitching artifacts and shadows. Furthermore, H.264 video compression is employed to reduce the data size of the video stream without sacrificing visual quality. Using the Real-Time Streaming Protocol (RTSP), the compressed stream is transmitted efficiently, supporting real-time remote monitoring and control of UGVs in dynamic battlefield environments. Experimental results indicate that the proposed system achieves high stability, flexibility, and low latency. With a wireless link latency of 30 ms, the end-to-end video transmission latency remains around 140 ms, enabling smooth video communication. The system can tolerate packet loss rates (PLR) of up to 20% while maintaining usable video quality (with latency around 200 ms). These properties make it well-suited for mobile communication scenarios demanding high real-time video performance.

Keywords

Unmanned ground vehicle (UGV) communication; video compression; packet loss rate (PLR); video latency; video quality

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