Bofan Wu
Papers
2
Total Citations
15
H-Index
1
About
Bofan Wu is a rising researcher in the field of multi-robot systems and autonomous navigation, with a focus on distributed control, optimization, and safety-critical motion planning. Their work addresses fundamental challenges in coordinating multiple robots under real-world constraints, particularly time-varying optimization and collision avoidance. In their highly cited 2023 paper, Wu introduced a hierarchical control framework that decomposes the complex distributed time-varying optimization problem into manageable network-layer and execution-layer subproblems, enabling multi-robot systems to achieve coordinated objectives while safely avoiding collisions. This work has garnered 14 citations, establishing a foundation for scalable multi-agent coordination. Most recently, in 2025, Wu proposed a safety-critical nonlinear model predictive control (NMPC) approach for car-like mobile robots navigating obstacle-filled environments with limited detection capabilities. By employing a temporary artificial reference within the detection region, this method ensures meaningful target tracking even under sensor constraints. Wu’s contributions are particularly valuable for applications in autonomous driving, warehouse robotics, and search-and-rescue operations, where robots must operate safely and efficiently in dynamic, partially observable environments.
Research Focus
Key Achievements
Top Papers
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