Professors at the University of Illinois at Urbana-Champaign are involved in a variety of highly impactful robotics-related projects. Here is a quick look at a few of them:

Ag Robot Speeds Data Collection, Analysis of Crops as They Grow

PI: Girish Chowdhary

A new lightweight, low-cost agricultural robot could transform data collection and field scouting for agronomists, seed companies and farmers. Traveling autonomously between crop rows, the robot measures the traits of individual plants using a variety of sensors, including cameras, transmitting the data in real time to the operator’s phone or laptop computer. A custom app and tablet computer that come with the robot enable the operator to steer the robot using virtual reality and GPS.

Vision-Centric Multi-Sensor Fusion for Navigation in Riverine Environments

PI: Soon-Jo Chung, Co-PI: Seth Hutchinson

Funded by the Office of Naval Research (ONR), this project is funding the creatiion of algorithms that are able to map an area, even when GPS signals aren’t available, such as inside a building or in remote areas. Researchers are testing the algorithms in the real world using the Navy’s Special Operations Craft-Riverine (SOC-R) boats in riverine environments. This type of boat is often used by the Navy to do short-range insertion and extraction of special operations forces in GPS-denied river environments.

Building Mechanical Bats for Construction Sites

PIs: Seth HutchinsonSoon-Jo ChungTimothy Bretl

These researchers have teamed up recently to develop a robot with the characteristics of a bat that would be able to supervise construction sites in a $1.5 million NSF grant. Chung has already been working on the process of developing winged robotic flight. In the past, he has developed airplanes that have mimicked bird flight in the way that they glide and land softly. This project is a continuation of previous work, but bat flight is even more complex than that of birds.

Cooperative Networked Control of Dynamical Peer-to-Peer Vehicle Systems

PI: Geir Dullerud

The goal of this Department of Defense Multidisciplinary University Research Initiative center was the development of a rigorous theoretical foundation, and scalable analytical tools and paradigms for construction of networked control for large numbers of autonomous and semi-autonomous air vehicles. The research is specifically aimed at the critical reliability and performance issues facing autonomous vehicle systems which operate in highly uncertain environments, and enables the vehicles to form teams, manage information, and coordinate operations including deployment, task allocation and search. The program produced both the fundamental theory necessary to allow systematic performance analysis, verification and validation of such systems, as well as algorithms for implementation, and design software.

Vision Containment for Robotic Mowing

PI: Seth Hutchinson, Co-PI: Soon-Jo Chung

Researchers are working on vision-based navigation and containment for robotic mowers, funded by John Deere. The work aims to ameliorate the concern of U.S. radio astronomers about the potential interference of the radio frequency signal that home robotic lawnmowers would create. There was recently wide media coverage on a complaint with the FCC filed by the National Radio Astronomy Observatory, urging the commission not to grant iRobot a waiver that would allow the Roomba lawnmowers to use a wireless beacon system that operates in the spectrum band of radio telescopes.

$7.5 million MURI

PIs: Tamer BaşarGeir DullerudCedric Langbort

These researchers and other Illinois professors and faculty from Georgia Tech, Stanford, UC-Berkeley and The University of Maryland, led a MURI to form a better understanding of how teams of humans and machines make decisions and develop more reliable and secure multi-layer networks where team interactions take place. Dullerud developed a distributed robotics testbed using a network of hovercraft and other autonomous vehicles that can interact with both human and machine-based decision makers.

Surveillance Network Research

PIs: Petros VoulgarisSoon-Jo Chung, Seth HutchinsonSteven LaValle

Illinois researchers lead a multi-university group in an approximately $1 million grant over three years from the Air Force Office of Scientific Research (AFOSR) to determine how sophisticated, unmanned surveillance vehicles can provide navy antiterrorism and force protection measures in harbors. The proposal looks at the complex problem of using a large network of decentralized autonomous agents with various sensing capabilities to work together to provide a massive amount of data.

Smart Systems for Field Monitoring and Surveillance

PIs: Petros Voulgaris   and Dušan Stipanović

Voulgaris and Stipanović lead a project funded by the Qatar National Research Fund to develop methods for safely coordinating networked vehicles. The researchers are working on developing algorithms that will guarantee safety in the presence of physical, collision avoidance and information constraints, and they will make the technology robust to communication uncertainty. This technology can be used in patrolling robots that sense dangerous leaks, such as H2S, coordinated fire extinguishing, coordinated oil spill cleaning and field coordinated surveillance.


PI: Naira Hovakimyan

Hovakimyan’s $1.5 million NASA-funded project to develop an integrated reconfigurable controller for vehicle resilience that will enhance next-generation aviation safety. The iReCoVeR architecture is based on Hovakimyan’s L1 adaptive control methodology, which is a promising technology for loss-of-control situations—the leading cause of commercial airline fatalities during the last 20 years.

Bretl teaches college-level robotics course to prison inmates

PI: Timothy Bretl

In spring 2013, CSL Associate Professor Timothy Bretl taught “Introduction to Robotics” to a group of 13 students-inmates at Danville Correctional Facility who were taking the course as part of the UIUC-sponsored Education Justice Program, which aims to bring higher learning to prisoners and provide outreach to inmates’ families in Chicago.

Students build competition-worthy UAV under CSL’s Hutchinson, Chung

PIs: Seth Hutchinson and Soon-Jo Chung

These researchers and their students designed and built a small drone aircraft to participate in the 2013 national Unmanned-Aerial-Surveillance (UAS) competition. They developed a solution they named Aerial-Based Intelligent Surveillance System (ABISS) to make their electrically-powered aircraft autonomous.

Cyber-Physical-Human Systems

PI: Alex Kirlik 

Kirlik is leading a $742,695 National Science Foundation (NSF) grant to study cyber-physical-human systems to further investigate how humans need to be added to the equation of automation for many aspects of our lives. The researchers are looking at ways to improve the interactions of the cyber and physical systems, specifically in the areas of flight simulation and anesthesiology.

Visual Servo Control, Planning with Uncertainty, Pursuit-Evasion Games

PI: Seth Hutchinson

Hutchinson has been studying robots since the early 1990s, with his research group pursuing topics including visual servo control, planning with uncertainty, pursuit-evasion games, as well as mainstream problems from path planning and computer vision. Recently, he developed an anytime algorithm for determining nearly optimal policies for total cost and finite time horizon partially observed Markov decision processes (POMDPs) using a sampling-based approach, as well as a a minimum uncertainty planning technique for mobile robots localizing with beacons.

Bretl, McCarthy win Best Manipulation Paper at IEEE Robotics and Automation conference

PI: Timothy Bretl

Bretl won the Best Manipulation Paper Award at the 2012 IEEE International Conference on Robotics and Automation. The paper, “Mechanics and Manipulation of Planar Elastic Kinematic Chains,” provides a mathematical model for solving a problem challenged researchers for years: How to enable robots to manipulate deformable, or flexible, objects. Bretl’s team discovered that by modeling the shape of a deformable object as the solution to an optimal control problem, and by studying the geometry of this problem, it became simple to describe all possible shapes. This result led to an algorithm for manipulation planning that was easy to implement and that performed well in practice.