Papers
2
Total Citations
16
H-Index
2
About
Hanwen Fan is a researcher advancing the intersection of computer vision and robotics, with a focus on intelligent automation for industrial and energy applications. Fan’s work addresses critical challenges in substation inspection and robotic manipulation. In a highly cited 2022 paper (12 citations), Fan proposed a multi-scale feature fusion algorithm for detecting meter targets in substations, significantly improving the accuracy and efficiency of inspection robots—a key enabler for smart grid modernization. More recently, in 2024, Fan introduced an improved Bald Eagle Search optimization algorithm to solve the complex, nonlinear inverse kinematics problem for robotic manipulators, offering a novel bio-inspired approach to achieving precise end-effector positioning. This work demonstrates Fan’s ability to blend optimization theory with practical robotics challenges. With a growing citation record, Hanwen Fan is establishing a reputation for developing practical, high-impact solutions that bridge algorithmic innovation and real-world deployment in automation and energy infrastructure.
Research Focus
Key Achievements
Top Papers
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