Bingyan Mao
Papers
2
Total Citations
57
H-Index
2
About
Bingyan Mao is a leading researcher in robotics and maintenance engineering, with a primary focus on advanced computational methods for remote manipulation in hazardous environments. Their work centers on developing hybrid optimization algorithms and structural analysis techniques to enhance the precision and reliability of robotic systems, particularly for nuclear fusion facilities. Mao’s most influential contribution is the hybrid differential evolution and particle swarm optimization algorithm, which achieved 39 citations for its innovative approach to solving numerical kinematics challenges in remote maintenance manipulators. This work has significantly improved the efficiency and accuracy of robotic arm control in extreme conditions. Additionally, Mao’s research on static stiffness modeling of the EAST articulated maintenance arm, using matrix structural analysis, has been cited 18 times, providing critical insights into the mechanical behavior of large-scale robotic systems. Their achievements have direct applications in fusion energy research, where precise maintenance is vital. By bridging optimization theory and practical engineering, Mao has established themselves as a key figure in advancing robotic autonomy and structural integrity for next-generation industrial and scientific applications.
Research Focus
Key Achievements
Top Papers
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