Papers
4
Total Citations
181
H-Index
4
About
Huihui Sun is a leading researcher in robotics, specializing in motion planning, cooperative manipulation, and intelligent control systems. Her work bridges deep reinforcement learning (DRL) and advanced robotics, with a focus on enhancing autonomy and precision in unstructured and dynamic environments. Sun’s most influential paper, “Motion Planning for Mobile Robots—Focusing on Deep Reinforcement Learning: A Systematic Review” (2021, 131 citations), provides a comprehensive survey of DRL-based motion planning, establishing a foundational resource for researchers advancing mobile robot intelligence. She has also made significant contributions to industrial robotics, including dynamic modeling and error analysis of cable-linkage serial-parallel palletizing robots (2020, 17 citations) and sliding mode control for multiple cooperative welding robot manipulators (2012, 17 citations), addressing complex tasks beyond single-robot capabilities. Her recent work on event-triggered reconfigurable reinforcement learning motion planning (2023, 16 citations) introduces adaptive strategies for unknown dynamic environments, pushing the boundaries of real-time robot decision-making. With over 180 total citations, Sun’s research is instrumental in developing more efficient, accurate, and autonomous robotic systems for both industrial and mobile applications.
Research Focus
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