Keli Shen
Papers
6
Total Citations
24
H-Index
3
About
Keli Shen’s research lies at the intersection of human balance biomechanics, humanoid robotics, and force-sensorless control. A central theme of their work is understanding and computationally modeling how humans use arm strategies to recover balance during quiet standing—a critical insight for both rehabilitation engineering and humanoid robot control. Their 2021 study, “Reproducing Human Arm Strategy and Its Contribution to Balance Recovery Through Model Predictive Control,” demonstrates how nonlinear model predictive control can replicate the arm’s role in maintaining stability, offering a framework for designing more resilient bipedal robots. Shen also introduced the Dynamic Reconfiguration Manipulability Shape Index (DRMSI), a novel metric for evaluating dynamic flexibility and posture in humanoid biped walking, applied in studies from 2016 to 2017. In parallel, their work on force-sensorless grinding accuracy, featuring resistance compensation, and the energy-saving benefits of elbow-bracing robot configurations, shows a practical engineering focus on precision and efficiency. With cumulative citations across these foundational studies, Shen’s contributions are shaping how we decode human motor strategies and translate them into robotic systems that move and recover balance more naturally.
Research Focus
Key Achievements
Top Papers
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- 6Analyses of biped walking posture by dynamical-evaluating index2 citations · 2017