Yifei Kong

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About

Yifei Kong is a researcher in robotics and intelligent control systems, with a primary focus on dynamic obstacle avoidance and fuzzy logic-based navigation. Their most-cited work introduces a novel second-order fuzzy control scheme that enables robots to autonomously avoid moving obstacles in unknown environments. By analyzing perceptual data—specifically changes in speed and deviation angle of detected obstacles—Kong’s approach enhances real-time decision-making and adaptability in complex, unpredictable settings. Although early in their citation impact, with 2 citations for their flagship 2015 paper, this work represents a foundational contribution to fuzzy control theory applied to mobile robotics, offering a computationally efficient alternative to traditional path-planning methods. Kong’s research bridges the gap between theoretical fuzzy systems and practical robotic applications, demonstrating how second-order fuzzy logic can improve responsiveness and safety in autonomous navigation. Their work is particularly relevant for researchers developing intelligent systems for search-and-rescue, autonomous vehicles, and service robotics, where dynamic obstacle avoidance remains a critical challenge.