Michael Drossakis
Papers
1
Total Citations
31
H-Index
1
About
Michael Drossakis has made significant contributions to the field of robotic vision and control, with a particular focus on enhancing the reliability of autonomous systems under real-world constraints. His key research areas include Image-Based Visual Servoing (IBVS), Nonlinear Model Predictive Control (NMPC), and robust control for aerial and underwater robotics. His most cited work, "Robustness analysis of model predictive control for constrained Image-Based Visual Servoing" (2014, 31 citations), addresses a critical challenge: ensuring stable vision-guided control in the presence of external disturbances—such as currents or turbulence—that commonly plague fast-moving or submerged robotic platforms. By rigorously analyzing the robustness of NMPC-based IBVS, Drossakis demonstrated how to maintain precise visual tracking even when constraints and uncertainties threaten performance. This work has implications for autonomous drones and underwater vehicles operating in unpredictable environments. His research bridges theoretical control analysis with practical robotic applications, offering engineers a framework to design more resilient vision-based systems. Drossakis’s contributions are particularly valuable for advancing the deployment of autonomous robots in challenging, disturbance-prone settings.
Research Focus
Key Achievements
Top Papers
- 1