Xiaoan Chen
Papers
11
Total Citations
240
H-Index
8
About
Xiaoan Chen is a robotics and control systems researcher whose work centers on robot force control, human-robot interaction, and intelligent automation. His most significant contributions lie in advancing compliance control methodologies for robotic systems operating in uncertain and dynamic environments. Chen's landmark 2019 paper on Dynamic Adaptive Hybrid Impedance Control — now with 81 citations — tackled the longstanding challenge of simultaneously managing transient contact force overshoots and steady-state tracking errors, a problem that had limited the practical deployment of robots in contact-rich tasks. This work was further refined in his 2020 study on smooth adaptive hybrid impedance control, which garnered 47 citations and introduced a pre-PID tuning framework for improved force response. Beyond force control, Chen has made notable strides in exoskeleton robotics, developing an infrared-sensor-based gait event detection system, and in human-robot collaboration, exploring eye-hand coordination and finite state machines for assembly tasks. His research on EMG-based teleoperation and gesture-driven grasping further reflects his broad commitment to intuitive human-robot interfaces. With over 230 cumulative citations, Chen's body of work represents a meaningful and growing contribution to intelligent robotic manipulation and collaborative automation.
Research Focus
Key Achievements
Top Papers
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