Current Research and Projects

Formation Control with Size Scaling

I am researching cooperative control strategies for teams of mobile agents. Some of my current research has focused on formation control strategies, in particular, we consider the problem of formation control when only a subset of the agents know the desired formation size. The remaining agents implement a cooperative control law using only local interagent position information such that the agents converge to the desired formation scaled by the desired size. The control laws that we design require only knowledge of relative displacement to neighboring agents, i.e. no communication among the agents. A subset of leader agents choose a desired scaling for the formation, and then all the agents move to a scaling of the desired formation. By allowing the size of the formation to change, the group can dynamically adapt to changes in the environment such as unforeseen obstacles, adapt to changes in group objectives, or respond to threats.

Formation Scaling

Pricing Schemes and Mechanism Design for Noncooperative Control

We consider agents acting noncooperatively in a networked, dynamic game setting and seek to design appropriate costs, mechanisms, or incentives to close the gap between what is possible with cooperative (i.e. team) control, and what happens in the noncooperative environment. We are currently investigating methods for designing quadratic costs imposed by a Stackelberg leader for linear dynamic games to ensure that a controller chosen by the leader (perhaps the optimal team controller) is a Nash Equilibrium of the resulting linear-quadratic game. We pose the problem as a convex optimization problem, and focus on pricing schemes that require the leader to only have knowledge of agents' inputs and not the system state. We further consider objectives such as costs that result in zero net profit for the leader and costs that rely only on local controls as defined by an interaction graph on the agents. We demonstrate our approach theoretically in the setting of energy management in buildings, and future work will investigate methods for applying our approach to a building on the UC Berkeley campus.

Switching Logic Synthesis for Networked Control

We investigate methods for synthesizing switching policies for systems of interconnected dynamical systems that are capable of operating in various modes. Such hybrid or switched systems often operate autonomously in each mode, and a supervisory controller switches between modes to guarantee certain criteria such as safety or performance. In particular, we consider sum-of-squares techniques for synthesizing semialgebraic switching surfaces and demonstrate our approach on a multiagent surveillance example and a cell transmission model of traffic. Future work will investigate additional applications and other techniques for switching logic synthesis.

Data Mining Class Project: Predicting Supreme Court Justice Votes from Oral Arguments

The purpose of this course project is to predict the votes of US Supreme Court justices using oral argument transcripts. By analyzing the Justices' comments and questions posed to each arguing party, we are able to provide predictions as to how the justices will vote. See the project webpage here.

Previous Research

NASA Jet Propulsion Laboratory, Guidance and Control Analysis Group

(Summer 2012)

This past summer, I worked at NASA's Jet Propulsion Lab in Pasadena, CA. I researched primitive body navigation focusing on state estimation techniques for landing spacecraft on primitive bodies such as comets and asteroids. Primitive bodies pose unique challenges for guidance, navigation and control as they are often irregularly shaped, have irregular gravitational fields, and can outgas, introducing severe disturbances. Additionally, in contrast to larger astronomical bodies that are well-studied, useful information such as landmark features, exact positioning, and inertial data are largely unknown. I investigated methods for state estimation that can incorporate data from a variety of sensors and is robust to outliers to allow sample return missions from these small bodies.

Georgia Robotics and Intelligent Systems Lab

(2009–2010)

I participated in Georgia Tech's Undergraduate Research Option under the advisement of Dr. Magnus Egerstedt in the Georgia Robotics and Intelligent Systems Lab. My three-semester project culminated in an Undergraduate Thesis entitled "Size-Switching in Formation Control" which explores decentralized methods for allowing a team of mobile agents in formation to collectively change formation size while maintaining formation shape.

EcoCAR Competition

(2008–2010)

I was a member of the Georgia Tech EcoCAR team, working primarily on the supervisory control for our hybrid-electric vehicle. The EcoCAR competition was a three-year advanced vehicle technologies competition established by the US DOE. I created simulations of the vehicle using steady-state modeling of the major vehicle components and developed supervisory control strategies. I also organized and was a member of an EcoCAR senior design team to work on specific controls-related aspects of the vehicle design.

Georgia Tech Research Institute

(2007–2009)

I worked at the Georgia Tech Research Institute (GTRI) for four semesters in the Communications and Networking Division (CND) of the Information Technology and Telecommunications Laboratory (ITTL) as part of the Georgia Tech Cooperative Education program. My research focused on developing technologies to dramatically increase public safety communications interoperability and on creating statewide communications plans and operating procedures. I also spent time working on the Direct To Discovery Project, a project focused on connecting K-12 students to university-level research through high-definition, interactive video conferencing with professors and researchers.

Project Links

Class Project: Predicting Supreme Court Justice Votes from Oral Arguments
Undergraduate Thesis
Senior Design Project [External Link]