Chencheng Dong
Papers
16
Total Citations
205
H-Index
7
About
Chencheng Dong is a leading researcher in bipedal robotics, specializing in high-dynamic locomotion, disturbance rejection, and adaptive control for humanoid robots. His work bridges the gap between human-like behavior and robotic stability, with major contributions in compliance control, running gait generation, and terrain adaptability. Dong’s most cited paper, “Resistant Compliance Control for Biped Robot Inspired by Humanlike Behavior” (2022, 53 citations), introduces a novel approach that mimics human resistance to sustained disturbances, addressing a critical flaw in traditional compliance control. His follow-up work on fuzzy logic-based adaptability (49 citations) tackles the challenge of variable stiffness and center-of-mass height regulation on complex ground. Dong has also pioneered unified control frameworks for high-dynamic motions, such as running and swift locomotion, with papers on online gait generation and direct collocation of reference-tracking dynamics (2023). His research on falling prediction using machine learning (14 citations) and knee-stretched walking via model predictive control (7 citations) further demonstrates his impact. With over 180 total citations, Dong’s innovations—including inertia-reduced leg designs and control moment gyroscopes for balance—are advancing the frontier of agile, resilient bipedal robots.
Research Focus
Key Achievements
Top Papers
- 1Resistant Compliance Control for Biped Robot Inspired by Humanlike Behavior53 citations · 2022
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- 5Falling Prediction based on Machine Learning for Biped Robots14 citations · 2021
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- 7A Unified Control Framework for High-Dynamic Motions of Biped Robots9 citations · 2021
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- 9Swift Running Robot Leg: Mechanism Design and Motion-Guided Optimization7 citations · 2023
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