Efstathios Bakolas
Papers
11
Total Citations
56
H-Index
5
About
Efstathios Bakolas is a robotics and control systems researcher whose work spans multi-robot coordination, trajectory optimization, stochastic control, and safe autonomous navigation. His research addresses some of the most pressing challenges in deploying autonomous robotic systems in real-world environments, with particular emphasis on developing mathematically rigorous frameworks that guarantee safety, scalability, and efficiency. Among his most notable contributions is his pioneering work on decentralized multi-robot navigation, where he has developed deadlock-free, safe control strategies using discrete-time control barrier functions — work that has attracted consistent citations since 2023. His research on covariance steering, including hierarchical optimal covariance control and Distributed Model Predictive Covariance Steering (DiMPCS), breaks new ground in managing uncertainty in multi-agent stochastic systems. His trajectory optimization methods for contact-constrained robotic systems reflect a sophisticated integration of optimal control and reachability analysis. More recently, Bakolas has explored machine learning acceleration of control algorithms, with TransformerMPC demonstrating how transformer architectures can dramatically reduce the computational burden of Model Predictive Control. With citations spanning foundational theory and cutting-edge applications, his cumulative body of work represents a meaningful and growing contribution to intelligent autonomous systems research.
Research Focus
Key Achievements
Top Papers
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- 7Distributed Model Predictive Covariance Steering5 citations · 2024
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- 9TransformerMPC: Accelerating Model Predictive Control via Transformers3 citations · 2025
- 10TransformerMPC: Accelerating Model Predictive Control via Transformers3 citations · 2024