Research

My main research area spans Control Theory, Robotics, Bayesian Methods for Machine Learning, Geometric Mechanics, and Dynamical Systems. I am particularly interested in the development of efficient control algorithms behind practical issues in robotics implementations with complex multi-robot systems.  My current research can be divided mainly into two lines: 

(1) Multi-Robot Systems: in particular, design and distributed implementations of controllers for coordination, tracking, collision avoidance of complex multi-robot systems, their applications in Unmanned Aerial and Ground Vehicles, and design of Robust Control Algorithms for fast and robust processing of data in Robotic Swarms. (2) Control-oriented by machine learning:  through the application of techniques from System Identification, Bayesian Inference, and Convex Optimization, with an emphasis on their applications to Correct-by-design Modeling and Online Learning of Complex Control Systems.

I apply my research in the fields of Automatic Control, Robotics, and Networked Nonlinear and Hybrid Systems.