Latency on Motion Synchronization in Game Engine-Driven Digital Twin Robotic Arms: Challenges and Techniques

Abstract

Ensuring precise and stable motion synchronization in game engine-driven digital twin robotic arms is challenging due to real-time data transmission delays. Various strategies—such as predictive modeling, network optimization, and robotic arm control techniques—have been proposed to address latency-aware motion synchronization. However, the absence of recent review papers in this area limits researchers’ ability to identify the most effective solutions for minimizing latency and enhancing system reliability. To fill this gap, we conducted a systematic literature review (SLR) to identify, analyze, classify, and summarize existing latency reduction techniques. A total of 125 research studies from reputable sources were reviewed to uncover recent trends in the field. We developed a taxonomy to group the identified methods based on common characteristics and provided concise summaries of each approach. Furthermore, this study outlines key research challenges and suggests future directions for improving synchronization accuracy. The findings offer a comprehensive and structured overview of existing solutions and serve as a valuable reference for researchers and practitioners aiming to advance real-time digital twin applications through game engine-based visualization.