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Center for Autonomy
Enabling high-impact research in autonomous system design
About
The Center for Autonomy (CfA) is Illinois's interdisciplinary hub for autonomy and robotics research and education in the Grainger College of Engineering at University of Illinois Urbana-Champaign. The CfA houses the Master of Engineering in Autonomy and Robotics, manages a number of robotics labs, fosters community, and helps incubate high-impact research endeavors.
From self-driving cars to intelligent robotic assistants to remote surgical systems, autonomous technology will revolutionize the way we live, work, and play. In order to enable this revolution, however, advancements in foundational research and workforce development must first take place to provide assured and certified-safe performance.
Application areas include:
UPCOMING & RECENT EVENTS
Robot Navigation in the Wild
Friday, October 30, 2026
2:00pm Central Time
Zoom Event
Speaker: Dinesh Manocha (University of Maryland)
In the last few decades, most robotics success stories have been limited to structured or controlled environments. A major challenge is developing robot systems that can operate in complex or unstructured environments, such as homes, dense traffic, outdoor terrain, and public places. In this talk, we give an overview of our ongoing work on developing robust planning and navigation technologies that use recent advances in computer vision, sensor technologies, machine learning, and motion planning algorithms. This includes an overview of our ongoing work to bridge this gap by addressing the core technical hurdles of autonomy, including perception failures in unstructured environments, the scarcity of real-world training data, the complexities of human-agent teaming, and the critical need for photorealistic simulation to overcome the sim-to-real gap. We present new methods that utilize multimodal observations from RGB cameras, 3D LiDAR, or robot odometry—alongside deep reinforcement learning or visual language models—to compute dynamically feasible, spatially aware actions. We highlight the performance of these systems across different applications: navigation in indoor scenes with dense crowds; long-range navigation on outdoor terrain for off-road autonomy. We conclude by highlighting a few challenges in developing autonomous robotic systems.