Papers
5
Total Citations
64
H-Index
3
About
Haifei Chen is a leading researcher in the field of space robotics and teleoperation systems, with a primary focus on overcoming the critical challenges of time delay, synchronization, and control in networked teleoperation. Chen’s work addresses the fundamental problem of maintaining telepresence and stability in space robot systems, where communication delays and intermittent interruptions are unavoidable. Their most cited paper (51 citations) introduces a mode switching-based symmetric predictive control mechanism for networked teleoperation space robot systems, tackling bilateral synchronization with unknown gravity and asymmetric random delays. More recently, Chen has pioneered the use of deep learning for position prediction in space teleoperation, developing a novel SAO-CNN-BiGRU-Attention algorithm (2024) that significantly improves telepresence by predicting robot positions to counteract asynchronous communication. Chen has also contributed to advanced sliding mode control for robotic manipulators, proposing an improved fixed-time nonsingular terminal sliding mode performance control method. With a growing body of work that combines classical control theory with modern AI techniques, Chen is making impactful strides toward enabling more reliable and responsive space teleoperation systems for future orbital missions.
Research Focus
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