Zhilun Yang

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About

Zhilun Yang is a leading researcher in intelligent robotics and autonomous navigation, with a particular focus on path planning algorithms for real-world applications. His most impactful work, the 2024 paper "Improved RRT* Algorithm for Disinfecting Robot Path Planning," has already garnered 23 citations, underscoring its significance in the field. In this study, Yang introduced the APF-GFARRT* algorithm—an innovative fusion of artificial potential field (APF) guided sampling and fuzzy adaptive expansion—that overcomes critical limitations in traditional RRT* methods, such as weak orientation and low search success rates. This breakthrough enhances the efficiency and reliability of disinfecting robots, directly addressing challenges in public health and automated sanitation. Yang's contributions lie at the intersection of robotics, artificial intelligence, and optimization, offering practical solutions for dynamic environments. His work not only advances theoretical understanding of sampling-based planning but also demonstrates tangible impact in robotics deployment. With a growing citation record and a focus on adaptive, real-time navigation, Zhilun Yang is establishing himself as a rising authority in intelligent robotic systems.