About

Patricio A. Vela is an Associate Professor in the School of Electrical and Computer Engineering at Georgia Tech. He is also an active member of the Institute for Robotics and Intelligent Machines. He directs the Intelligent Vision and Automation Lab (IVALab), where the research focus revolves around algorithms and algorithmic formulations for perception and control with application to robot autonomy.

His graduate studies were in geometric nonlinear control with application to biologically-inspired locomotion, where averaging theory played a prominent role in reducing time-periodic control signals to time-invariant forms. In the simpler time-invariant form, traditional nonlinear control methods could be applied to achieve closed-loop control for this class of systems. His post-doctoral research involved a detour into computer vision, specifically controlled active vision and visual tracking. After becoming a faculty member at Georgia Tech, this line of research continued into the first few years. Emphasis was on exploiting the underlying geometric and functional representations of point-based and segmentation-based tracking for deriving real-time target tracking solutions. The computer vision research has slowly evolved to encompass robotic applications as opposed to automated decision support tools, but continues to embody controlled active vision principles.

Currently, his group's research revolves around closed-loop aspects related to robot autonomy with an emphasis on perception-in-the-loop algorithms and the use of machine learning for control of robotic systems with uncertain properties or uncertain robot-world interactions. Numerical methods and real-time implementation are critical factors considered in the research efforts. The robot platforms include traditional platforms (ground and aerial) as well as biologically-inspired platforms (snake, salamander-like). Ultimately, the research aims to bridge the theory-practice gap through advances in numerical and algorithmic design.

Classes

Online course material can be found in the classes Wiki. Courses actively taught on a regular basis include:

ECE4560		Introduction to Robotics and Automation
ECE4580		Computational Computer Vision
ECE6554		Adaptive Control

Course taught or involved with in the past include:

ECE4011/12		Senior Design
ECE3084		Introduction to Signals and Systems

For serious and proactive students whose curricular interests align with the group's research directions, special topics projects may be considered.

Professional Experience

2011 -	Associate Professor
2005 - 2011	Assistant Professor
2003 - 2005	Post-Doctoral Researcher
	School of Electrical and Computer Engineering
	Georgia Institute of Technology

Education

2003	PhD	Control and Dynamical Systems
1998	BS	Engineering and Applied Sciences
		California Institute of Technology