Texas Robotics provides world-class education and pursues innovative research emphasizing long-term autonomy and human-robot interaction while leveraging UT Austin’s breadth to support a broad range of industrial applications.
The Lab focuses on the development of robotic devices, based on biomechanical analyses, to assist in rehabilitation, to improve prostheses design, and to provide fitness opportunities for the severely disabled.
The u-t autonomous group's research is on the theoretical and algorithmic aspects of design and verification of autonomous systems. It embraces the fact that autonomy does not fit traditional disciplinary boundaries, and has made numerous contributions in the intersection of formal methods, controls and learning.
This lab explores the mechanisms that enable intelligence in embodied agents. Inspired by biological intelligence, we developed robotic algorithms that improve robot autonomy in perception, control, knowledge representation and decision making through learning. Our goal is to create robotic helpers that enhance human everyday life.
The ARTS lab develops high dexterity and situationally aware continuum manipulators, soft robots, and instruments especially designed for less invasive treatment of various surgical interventions.
The RPL lab aims at building general-purpose robot autonomy in the wild. We develop intelligent algorithms for robots and embodied agents to reason about and interact with the real world.
The CLeAR lab focuses on the intersection between control theory, machine learning, and game theory to design high performance, interactive autonomous robots.
Our long-term goal is to develop robotic systems that are truly collaborative partners with human operators, focusing on technology for surgical intervention and medical training.
The focus of our research is on the direct use of human brain signals for human-robot interaction and control of neuroprostheses. The overarching objective of our research is to bring brain-machine interfaces (BMI) out of the laboratory to augment human capabilities, recover from insults to our central nervous system, and facilitate user’s acquisition of BMI skills.
The Swarm Lab works on collaborative perception, learning, and control between fleets of networked robots. We also work on robust computer vision and model predictive control for drones. Our research spans optimal control, energy-efficient deep learning, 5G wireless networking, and computer vision. We regularly publish in venues such as ICML, Neurips, RSS, CORL, MLSys, ICRA, and IROS. The Swarm Lab collaborates with local Austin startups, Lockheed Martin, Cisco, Intel, Honda Research and a variety of other corporate sponsors. We are always recruiting new students!