Automation & Control

Automation & Control combines engineering with machine-learning in order to provide industrial systems with the information necessary to work in an automatic and controlled manner. Research areas include: atomic force microscopy, bio-inspired control, discrete-event systems, formal languages for robot mission specification, hybrid systems, image-guided surgery, networked control systems, robot path planning and control, robotic swarms, and UAV flight control.

CPS: Synergy: Data Driven Intelligent Controlled Sensing for Cyber Physical Systems

The goal of this project is to develop the foundations of a control and optimization science base for sensor networks viewed as complex systems operating in an uncertain and potentially adverse environment. The approach taken is a combination of addressing fundamental research issues while maintaining a focus on a specific target application domain, a manufacturing […]