Papers
7
Total Citations
209
H-Index
5
About
Nan Gu is a researcher specializing in autonomous marine and mobile robotics, with a focus on cooperative control, path following, and robust disturbance rejection for unmanned surface vehicles (USVs) and mobile robot systems. His work bridges rigorous theoretical frameworks with real-world experimental validation, making it particularly impactful in the field of autonomous systems. Gu's most influential contribution, "Anti-disturbance Coordinated Path-following Control of Robotic Autonomous Surface Vehicles" (2019, 86 citations), established a landmark guidance and control methodology for networked underactuated ASVs operating under realistic ocean disturbances — a challenge central to practical maritime autonomy. His follow-up work on path-guided containment maneuvering (2020, 61 citations) extended these ideas to multi-robot formations with multiple virtual leaders, demonstrating versatility across platforms. More recently, Gu has advanced data-driven and model-free adaptive control strategies, including safety-certified learning approaches incorporating neurodynamic optimization (2024), reflecting a forward-looking embrace of intelligent control paradigms. His nonlinear observer designs and hardware-in-the-loop experimental results further underscore a commitment to deployable, experimentally verified solutions. With over 200 cumulative citations across his key works, Gu's research is shaping the next generation of resilient, cooperative autonomous vehicle systems.
Research Focus
Key Achievements
Top Papers
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- 2Path-Guided Containment Maneuvering of Mobile Robots: Theory and Experiments61 citations · 2020
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