Papers
1
Total Citations
3
H-Index
1
About
Yuhu Wu is a leading researcher in control systems and robotics, with a primary focus on safety-critical control, model predictive control (MPC), and autonomous navigation. His most impactful work addresses the fundamental challenge of ensuring safe, real-time trajectory tracking and obstacle avoidance in multi-robot systems, particularly for wheeled mobile robot formations operating in confined spaces. By developing novel safety-critical MPC frameworks, Wu has overcome the limitations of traditional offline optimization methods, enabling robust online decision-making that guarantees collision avoidance while maintaining formation integrity. This research, published in 2025 and already garnering early citations, has significant implications for warehouse logistics, autonomous driving, and cooperative drone swarms. Wu’s contributions are distinguished by their practical focus on bridging theoretical safety guarantees with real-time computational feasibility, making his work essential for engineers and researchers developing next-generation autonomous systems. His growing citation record reflects the increasing demand for reliable, scalable solutions in safety-critical robotics, positioning him as a key innovator in the field of autonomous multi-agent coordination.
Research Focus
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