Papers
7
Total Citations
185
H-Index
7
About
Yong Cui is a versatile robotics and artificial intelligence researcher whose work spans autonomous underwater systems, miniature robotics, and intelligent trajectory prediction. His early career established foundational contributions to underwater vehicle-manipulator systems (UVMS), where his unified force control frameworks — combining impedance and adaptive control strategies for six-degree-of-freedom autonomous underwater vehicles paired with robotic arms — garnered sustained scholarly attention, collectively accumulating over 100 citations across multiple publications. These works remain important references for researchers tackling the complex dynamics of subsea manipulation tasks. Cui's research portfolio has since expanded into cutting-edge domains. His 2023 work on a 3.4-millimeter flea-sized robot, capable of powerful jumping and fast crawling through a novel high-voltage pulsed actuator, demonstrates his ongoing commitment to pushing the boundaries of miniature locomotion systems. Meanwhile, his 2022 contribution on spatio-temporal graph convolution networks for pedestrian multimodal trajectory prediction addresses critical challenges in autonomous driving and service robotics, reflecting his growing engagement with machine learning applications. Spanning two decades and multiple disciplines — from underwater robotics to micro-scale machines to AI-driven motion prediction — Cui's body of work illustrates a researcher continually exploring the frontiers of intelligent and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2A unified force control approach to autonomous underwater manipulation37 citations · 2001
- 3Impedance control of underwater vehicle-manipulator systems (UVMS)27 citations · 2003
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- 7A unified force control approach to autonomous underwater manipulation14 citations · 2002