Papers
13
Total Citations
107
H-Index
7
About
Sheng Dong is a robotics researcher whose work centers on the dynamic locomotion and control of legged robots, with a particular focus on bipedal and humanoid systems. His major contributions lie in advancing robust gait generation and real-time balance recovery for hydraulic-driven biped robots. Dong’s most cited work, “Structural Design and Kinematics Simulation of Hydraulic Biped Robot” (23 citations), introduces the NWPUBR-1 humanoid, a 12-DOF platform designed with modular joint sensors. He has pioneered the use of learning-based model predictive control (13 citations) and nonlinear state estimation frameworks (11 citations) to enhance robot stability. His research on flexible model predictive control and online gait adjustment, inspired by human anti-disturbance strategies, addresses critical challenges in dynamic walking. Notably, Dong’s 2025 review on quadruped robots highlights his broader impact on legged locomotion, emphasizing environmental adaptability. With over 100 cumulative citations across his top papers, Dong is recognized for bridging theoretical control methods with practical engineering solutions, making him a key figure in the development of resilient, torque-controlled biped robots.
Research Focus
Key Achievements
Top Papers
- 1Structural Design and Kinematics Simulation of Hydraulic Biped Robot23 citations · 2020
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- 3A nonlinear state estimation framework for humanoid robots11 citations · 2022
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