Fenfen Yan

Papers

Total Citations

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About

Fenfen Yan is a researcher advancing the frontiers of autonomous robotics, with a primary focus on cognitive navigation and adaptive path planning in complex environments. Her most-cited work, "Autonomous robot navigation based on a hierarchical cognitive model" (2022), introduces the Hierarchical Cognitive Navigation Model (HCNM), a novel framework that enhances a mobile robot's self-learning and self-adaptive capabilities. By employing a divide-and-conquer strategy, Yan’s model decomposes intricate path planning tasks into manageable sub-tasks, enabling robots to navigate unknown terrains with greater efficiency and intelligence. This contribution has garnered 6 citations, marking a foundational step toward more autonomous and resilient robotic systems. Yan’s research sits at the intersection of cognitive science and robotics, offering practical solutions for real-world applications such as search-and-rescue and industrial automation. Her work not only addresses the critical challenge of robot autonomy but also inspires future explorations into hierarchical learning architectures. For students and researchers, Yan’s approach exemplifies how structured cognitive models can bridge the gap between theoretical AI and tangible robotic performance.