Petros G. Voulgaris
University of Illinois Urbana-Champaign, University of Nevada, Reno
Papers
8
Total Citations
362
H-Index
6
About
Petros G. Voulgaris is a leading figure in the control of multi-robot networks, where his work masterfully bridges the gap between rigorous theoretical guarantees and practical, real-world constraints. His research centers on distributed coordination, safe autonomy, and resilient estimation, with a particular focus on enabling teams of robots to achieve complex objectives while navigating obstacles, maintaining communication, and ensuring safety. His most impactful contribution is the introduction of Lyapunov-like barrier functions for multi-agent control, a framework detailed in his highly cited 2015 paper (246 citations) that provides a powerful, set-theoretic method for encoding multiple, non-trivial safety and performance constraints directly into the control law. Voulgaris has also made seminal contributions to target assignment, establishing distance-optimality guarantees for robotic networks under communication and sensing limitations. His work extends into attack-resilient estimation for safety-critical systems and, most recently, into the intersection of safe control and machine learning, exploring path integral methods with stochastic control barrier functions and adversarial robustness for autonomous vehicles using reinforcement learning. Through a career defined by solving foundational problems in multi-agent systems, Voulgaris has profoundly shaped how we design safe, efficient, and resilient robotic networks.
Research Focus
Key Achievements
Top Papers
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- 5Path Integral Methods with Stochastic Control Barrier Functions14 citations · 2022
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