Zirui Xu
Papers
4
Total Citations
40
H-Index
4
About
Zirui Xu is a robotics and autonomous systems researcher whose work sits at the intersection of submodular optimization, multi-robot coordination, and decision-making under uncertainty. His research addresses one of the most pressing challenges in modern autonomy: enabling teams of robots to coordinate effectively in dynamic, unpredictable, and adversarial environments where information is limited and computational resources are constrained. Among his most significant contributions is pioneering resource-aware distributed submodular maximization, introducing the first algorithmic framework that allows multi-robot systems to make high-quality collective decisions despite onboard resource limitations. His work on online submodular coordination with bounded tracking regret (14 citations) established rigorous theoretical guarantees for robot teams operating in environments with unknown or adversarial future evolution. Complementing this, his bandit submodular maximization framework extends coordination capabilities to partially observable settings, where robots must act on incomplete environmental information. Beyond coordination, Xu has contributed to robust motion planning through his RRT-based intermittent planning framework, designed for robots with unknown dynamics navigating changing environments. Collectively accumulating over 40 citations across recent publications, his research lays foundational groundwork for deploying reliable autonomous systems in real-world, unstructured conditions — a critical step toward practical multi-robot autonomy.
Research Focus
Key Achievements
Top Papers
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