Christos G. Cassandras
Papers
12
Total Citations
159
H-Index
6
About
Christos G. Cassandras is a prominent researcher whose work sits at the intersection of autonomous systems, optimal control, and safety-critical robotics. His research has made substantial contributions to trajectory optimization, multi-agent coordination, and formal methods for autonomous vehicles and robotic systems. Cassandras has been particularly influential in advancing Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs) as practical tools for guaranteeing safety while optimizing performance in real-time constrained systems — work reflected in highly cited papers such as his studies on feasibility-guided learning and event-triggered control for systems with unknown dynamics (25–26 citations each). His investigations into robotic surveillance with Linear Temporal Logic specifications and spatio-temporal trajectory optimization (24–30 citations) demonstrate a sophisticated blend of formal verification and control theory. Cassandras has also made meaningful advances in Connected and Automated Vehicle (CAV) coordination and energy-efficient robot path planning in complex environments. His prolific output, spanning foundational theory to applied robotics and intelligent transportation, has cemented his reputation as a leading voice in the autonomous systems research community, with his most impactful works collectively drawing hundreds of citations.
Research Focus
Key Achievements
Top Papers
- 1Receding horizon surveillance with temporal logic specifications30 citations · 2010
- 2Event-Triggered Control for Safety-Critical Systems With Unknown Dynamics26 citations · 2022
- 3Feasibility-Guided Learning for Constrained Optimal Control Problems25 citations · 2020
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- 5Applications to Robotics20 citations · 2023
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- 9Learning Feasibility Constraints for Control Barrier Functions4 citations · 2023
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