Controls, Instrumentation and Robotics

The Control, Instrumentation, and Robotics (CIR) area seeks to promote research and education into identifying fundamental principles and methodologies that enable systems to exhibit intelligent, goal-oriented behavior, and developing innovative instruments to monitor, manipulate, and control systems. Our focus is on system-level behavior emerging primarily from interactions - unexplainable from individual component behavior alone.
Overview

CIR leverages three core competencies in service to diverse needs in such areas as healthcare, security, education, space and ocean exploration, and autonomous systems in air, land, and underwater. These three core competencies are:

(*) Methodologies for understanding system behavior through physical modeling, identification, and estimation
(*) Technologies for sensors and sensor networks; actuators and energy transducers; and systems for monitoring, processing, and communications information
(*) Fundamental theories and methodologies for analyzing, synthesizing, and controlling systems; learning and adapting to unknown environments; and achieving task goals

Among the research challenges currently being explored are:

(*) Super-muscle actuators -- We seeks to create new actuator technology that greatly surpasses biological muscle in terms of stress, energy density, efficiency, response speed, and degrees of freedom. Recent development of novel actuator materials, such as conductive polymers and dielectric elastomers, is a first step towards our goal, opening up new possibilities of activating diverse objects, including garments, surgical tools, and robots.

(*) Ocean exploration and large-scale, real-time monitoring -- This multi-investigator project is being conducted in collaboration with the Center for Ocean Engineering. It involves the development of autonomous unmanned underwater vehicles and sophisticated sensors to enable the collection of information in waters where researchers cannot go.

(*) Multi-modal imaging -- Imaging is the key to understanding system behavior in a parallel sense and is applicable to a wide range of contexts, from biomedical diagnostics to homeland security to space exploration. "Multi-modal" imaging refers to the combination of optical, acoustic, and magnetic imaging technologies and techniques. By jointly optimizing physics and algorithms for extracting maximum but relevant information, we can extract efficient, "reduced model" representations of the observed systems - critical for imaging micro- and nano-scale objects, and super-macro objects of planetary scale.