Yong Fan

Shandong Institute of Automation, Shandong Jiaotong University

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About

Yong Fan is a robotics researcher whose work spans multi-robot systems, autonomous navigation, and legged robotic platforms. His early contributions focused on formation control for multiple mobile robots, introducing a motor schema-based architecture with four primitive behaviors — goal pursuit, formation maintenance, and obstacle avoidance — that established foundational principles for coordinated robot movement, earning 32 citations since 2003. Building on this groundwork, Fan later addressed the challenges of dynamic path planning for social robots operating in home environments, proposing an improved Rapidly-exploring Random Tree (RRT) algorithm capable of navigating complex, obstacle-rich spaces in real time, a contribution that has accumulated 22 citations since its 2020 publication. His more recent work demonstrates a broadening scope toward sophisticated physical systems, with a robust control framework for legged mobile manipulators that integrates virtual model control and whole-body control to achieve compliant, stable locomotion and manipulation — already garnering 20 citations since 2023. Across his career, Fan has consistently advanced the practical autonomy of robotic systems, bridging theoretical control strategies with real-world deployment challenges in dynamic and unstructured environments.