About

Vasileios Tzoumas is a robotics and autonomous systems researcher whose work spans robust spatial perception, resilient multi-robot coordination, and safe control under uncertainty. He is perhaps best known for his contributions to outlier-robust estimation, most notably his highly cited 2020 paper on Graduated Non-Convexity for robust spatial perception (306 citations), which revolutionized how robotic systems handle corrupted sensor data by enabling global outlier rejection without sacrificing computational tractability. This work has become a cornerstone reference in robot perception and computer vision communities. A significant thread of Tzoumas's research addresses resilient multi-robot planning under adversarial conditions, including denial-of-service attacks and sensor failures. His work on resilient submodular and non-submodular maximization provides rigorous algorithmic guarantees for robot teams operating in hostile or unpredictable environments, blending combinatorial optimization with practical autonomy challenges. More recently, he has extended these ideas to online coordination with bounded regret and resource-aware distributed decision-making, tackling the computational realities of deploying large robot swarms. His 2023 work on safe non-stochastic control further demonstrates his commitment to principled guarantees for real-world autonomous systems. Collectively, Tzoumas's research establishes him as a leading voice in making autonomous robots simultaneously robust, resilient, and theoretically well-grounded.

Research Focus

Key Achievements

9
H-Index
22
Papers
594
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection
306 citations · 2020
📈 Most Prolific Year: 2018 (5 Papers)
🤝 Key Collaborators: 19
🏛 Institutions: Decision Systems (United States), University of Pennsylvania, Massachusetts Institute of Technology, University of Michigan–Ann Arbor

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago