Autonomous systems and Artificial Intelligence research at the University of Utah focuses on enabling robots to learn by interacting with their environment, gathering information, and improving performance over time. Research includes reinforcement learning, sim2real transfer, imitation learning, robustness to uncertainty, computer vision and perception, long-horizon motion planning and control, and dexterous manipulation.

Aligned, Robust, and Interactive Autonomy (ARIA) Lab

Daniel Brown, PhD

Assistant Professor, School of Computing

The Aligned, Robust, and Interactive Autonomy (ARIA) Lab focuses on developing algorithms that enable robots and other AI systems to safely and efficiently interact with, learn from, teach, and empower human users. Our research spans the areas of human-robot interaction, reward and preference learning, imitation learning, human-in-the-loop reinforcement learning, and AI safety. We develop both algorithms and theory, deploy these algorithms on robot hardware platforms, and run user studies to better understand human factors. We are interested in a diverse set of applications including domestic service robots, assistive and medical robotics, bio-inspired swarms, autonomous driving, and personal AI assistants.

Drew Research Lab

Daniel Drew, PhD

Assistant Professor, Electrical & Computer Engineering
Lab Website: The Drew Research Lab for Autonomous Robotic Millisystems

The driving goal behind our work is to make insect-scale robots truly useful as tools in industrial, commercial, and personal settings. This means not only overcoming the extreme resource constraints imposed by their scale, but also delivering capabilities that are wholly unique. Our work ties numerical simulation together with cutting-edge microfabrication and meso-scale assembly techniques, exploring novel actuation, communication, and sensing modalities for holistically-designed systems. Sometimes we look to nature for inspiration, like in the design of multifunctional components for acoustic communication; often we look beyond it, like in the creation of silent, solid-state atmospheric ion thrusters for flight. In all cases, energy and payload constraints demand systems designed from the ground up, tightly integrated, and at the bleeding edge of possibility.

Artificial intelligence and Robotics in Medicine Lab (ARMLab)

Alan Kuntz, PhD

Assistant Professor, School of Computing
Lab Website: Artificial intelligence and Robotics in Medicine Lab (ARMLab)

The Kuntz Lab is an interdisciplinary research lab in the Robotics Center and Kahlert School of Computing at the University of Utah focusing on robotics and computational methods with medical applications. Research areas include healthcare applications of artificial intelligence, design optimization, and robot motion planning.