Zhangyi Chen
Papers
5
Total Citations
38
H-Index
3
About
Zhangyi Chen is a robotics researcher whose work centers on advancing human-robot interaction, teleoperation systems, and intelligent control interfaces. His major contributions lie in developing intuitive, wearable-based control methods that enhance the reliability and efficiency of teleoperated robots. Chen’s most cited paper, “IMU Motion Capture Method with Adaptive Tremor Attenuation in Teleoperation Robot System” (2022, 18 citations), introduces a novel interface that suppresses physiological tremors for more precise remote control. He further improved teleoperation with an object detection and localization method based on improved YOLOv5 (2022, 13 citations), boosting execution efficiency. Chen has also advanced myoelectric gesture recognition for robust human-robot interaction (2025, 4 citations) and developed a learning-based slip detection system using tactile sensors for stable robotic grasping (2025, 2 citations). His recent work on an intuitive teleoperation interface using a wearable myoelectric armband (2025, 1 citation) underscores his commitment to making robot control more natural and accessible. Through these innovations, Chen is helping bridge the gap between human intent and robotic action, with applications ranging from assistive robotics to industrial automation.
Research Focus
Key Achievements
Top Papers
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