Rui Yuan Fan

Papers

Total Citations

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About

Rui Yuan Fan is a robotics researcher whose work focuses on autonomous navigation and path planning in complex, unknown environments—critical for advancing search-and-rescue operations. Fan’s most cited paper, “Search and Rescue Robot Path Planning in Unknown Environment” (2012, 4 citations), introduces a bionic learning algorithm that combines a Growing Self-Organizing Map (GSOM) for environmental cognitive mapping with the heuristic A* algorithm for global optimal pathfinding. This hybrid approach enables robots to dynamically adapt to unfamiliar terrains, a key challenge in disaster response scenarios. While citation counts are modest, the work’s conceptual contribution lies in bridging neural-inspired learning with classical search methods, offering a practical framework for real-time robotic decision-making. Fan’s research underscores the importance of integrating adaptive mapping with efficient path optimization, laying groundwork for future autonomous systems in hazardous settings. This study remains a reference point for researchers exploring bio-inspired algorithms in mobile robotics, particularly for applications requiring rapid environmental understanding and safe navigation.