Jiyuan Yan

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About

Jiyuan Yan is a researcher at the forefront of intelligent robotics and computer vision for critical infrastructure maintenance. His work centers on developing advanced algorithms to enhance the autonomy and precision of live-line working robots, particularly for high-risk tasks on power transmission lines. Yan’s major contribution lies in the integration of lightweight deep learning models with practical robotic systems. His most cited paper, "An enhanced YOLOv8‐based bolt detection algorithm for transmission line" (2024, 10 citations), addresses the crucial challenge of balancing algorithm efficiency with detection accuracy for real-time robotic operations. This work proposes a streamlined YOLOv8 variant specifically designed for identifying small, critical components like bolts in complex outdoor environments. Further demonstrating his focus on operational safety, his research on "Target Ranging Method for Live-Line Working Robots" (2024, 2 citations) introduces a novel visual assistance system for precise distance measurement, enabling robots to perform delicate tasks at elevated heights. By tackling the dual problems of robust detection and accurate spatial localization, Jiyuan Yan is making significant strides toward safer, more reliable automated maintenance of our electrical grid.