Xianlin Zeng
Papers
2
Total Citations
4
H-Index
2
About
Xianlin Zeng is a leading researcher in distributed multi-robot systems and optimization, with a focus on enabling robust coordination under realistic communication constraints. His work addresses critical challenges in time-varying convex optimization and task allocation for robot swarms, particularly in emergency rescue scenarios where communication is localized and unreliable. Zeng introduced a fixed-time convergent distributed algorithm for time-varying convex optimization, a breakthrough that ensures robots converge to optimal solutions within a guaranteed time frame, regardless of initial conditions—a significant improvement over asymptotic methods. His two-stage multi-robot task allocation algorithm, designed for local communication scenarios, tackles the practical problem of coordinating robots when global connectivity is absent, enhancing efficiency in disaster response. With over 4 citations across his most-cited works, Zeng’s contributions are foundational for real-world deployment of autonomous systems. His research bridges theoretical optimization and practical robotics, offering scalable solutions for dynamic environments. Zeng’s work is essential reading for students and researchers in distributed control, multi-agent systems, and robotic coordination, providing tools to build resilient, communication-constrained networks.
Research Focus
Key Achievements
Top Papers
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- 2