Chengqian Xue
Papers
7
Total Citations
598
H-Index
5
About
Chengqian Xue is a leading researcher in physical human–robot interaction (pHRI), with a focus on making robots safer, more compliant, and more intuitive to work alongside. Their work centers on admittance and impedance control, Bayesian estimation of human motion intention, and adaptive neural network strategies for constrained and collaborative tasks. Xue’s most influential contribution is the admittance-based controller for pHRI in constrained task spaces, which has garnered 294 citations for its elegant use of a soft saturation function to generate differentiable reference trajectories. They also pioneered a Bayesian method to estimate human impedance and motion intention, achieving 150 citations by fusing prior stiffness knowledge with real-time data. Further notable achievements include adaptive neural impedance control for series elastic actuator (SEA)-driven robots and cooperative control of dual-arm robots across teleoperation, co-carry, and assembly regimes. With over 588 total citations across their top papers, Xue’s research directly advances the safety and autonomy of collaborative robots in manufacturing and assistive settings. Their work is essential reading for anyone developing human-aware robotic systems that must adapt to uncertain environments and human partners.
Research Focus
Key Achievements
Top Papers
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- 4Adaptive NN impedance control for an SEA-driven robot50 citations · 2020
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