Shangru Yang
Papers
2
Total Citations
29
H-Index
2
About
Shangru Yang is a researcher in robotics, with a primary focus on the locomotion and control of hydraulic quadruped robots. His work centers on enhancing the dynamic stability and environmental adaptability of these complex machines, particularly through active compliance control and state estimation. In his most-cited paper, "Research and Improvement on Active Compliance Control of Hydraulic Quadruped Robot" (2021, 20 citations), Yang proposed novel methods to improve a robot’s ability to interact safely and effectively with uneven terrain, a critical challenge in field robotics. He further advanced this area in "State estimation of hydraulic quadruped robots using invariant-EKF and kinematics with neural networks" (2023, 9 citations), where he integrated invariant extended Kalman filters with neural network-based kinematics to achieve more accurate and robust state estimation. This work bridges classical control theory with modern machine learning, offering a practical pathway for real-time, reliable robot operation. Yang’s contributions are particularly relevant for applications in search-and-rescue, industrial inspection, and exploration, where hydraulic robots must navigate unpredictable environments. His research demonstrates a strong commitment to solving fundamental problems in legged locomotion, making him a notable emerging voice in the field of robotic control and estimation.
Research Focus
Key Achievements
Top Papers
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