Chin Cheng Chen
Papers
2
Total Citations
35
H-Index
2
About
Chin Cheng Chen is a leading researcher in humanoid robotics, specializing in bipedal locomotion and trajectory generation. His work centers on developing sophisticated models that enable humanoid robots to walk with greater stability and naturalness, bridging the gap between mechanical systems and human-like motion. Chen’s major contributions include the introduction of multi-mass models with angular momentum, which significantly reduce modeling errors compared to traditional approaches. His most cited paper, “Biped Walking Trajectory Generator Based on Three-Mass With Angular Momentum Model Using Model Predictive Control” (2015, 27 citations), demonstrates a novel method for achieving high zero moment point (ZMP) tracking accuracy and immediate trajectory generation. Building on this, his 2017 work on a five-mass model using feedback-feedforward control further refines walking dynamics by minimizing nonminimum phase properties, enhancing frequency response. With a combined citation impact of over 35 citations, Chen’s research is foundational for advancing quasi-natural humanoid walking, offering practical solutions for real-time control in robotics. His work is essential reading for students and engineers aiming to push the boundaries of autonomous, human-like robot mobility.
Research Focus
Key Achievements
Top Papers
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