Research

 

Projects

Image-based Modeling, Control and Calibration for High Speed Scanning Probe Microscopy (G. M. Clayton)

Scanning probe microscopes (SPMs) are a key enabling tools for nanotechnology because of their ability to image, manipulate, and fabricate nano-scale objects. The primary impediment to the increased use of these devices is limited throughput (limited speed). In order to overcome this limitation, Dr. Garrett M. Clayton is developing methods that use SPM images to model, control and calibrate SPM devices. Current theoretical and experimental investigations are focused on the measurement and control of general two dimensional trajectories.

Unmanned Vehicle Modeling and Control Using Vision-based Information (G. M. Clayton)

Images contain information not only about the position, orientation and motion of the objects in the image, but about the position, orientation and motion of the imaging device itself. In order to improve the performance of unmanned vehicles (UMVs), Dr. Garrett M. Clayton is developing modeling and control methods which exploit the UMV vision system, e.g. extract position, orientation and motion from the images. Initial investigations are focused on developing input-output dynamic models of UMVs from the vision system, which can be used to develop feedforward and feedback control systems, enabling higher-speed, higher-accuracy UMV operation.

Piezoelectric Actuator Vibration Suppression (C. Nataraj and G. M. Clayton)

Piezoelectric actuators have been widely used for structural vibration suppression. In this project, funded by the Turbo Research Foundation, Dr. C. Nataraj and Dr. Garrett M. Clayton are developing control algorithms for these vibration controlling piezoelectric patches. Of specific interest are the theoretical development and experimental implementation of partial differential equation control methods such as boundary control.

The Microsoft Kinect as a Mobile Robotics Sensor (G. M. Clayton and J. Peyton Jones)

The ability of autonomous systems to understand and navigate in uncertain environments is heavily dependent on the sensors for detecting both moving and stationary obstacles. The recent release of the Microsoft Kinect provides a powerful vision sensor which captures both camera and depth images of the environment. Dr. Garrett M. Clayton and Dr. James Peyton Jones (ECE) are working on hardware and software solutions that enable the use of the Kinect in mobile robotic applications.