Research
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.
Human Centered Robotics Lab
The Human Centered Robotics lab designs humanoid robots and researches bipedal locomotion.
Learning Agents Research Group
The Learning Agents Research Group pertain to machine learning (especially reinforcement learning) and multiagent systems.
Nuclear Robotics Group
The Nuclear and Applied Robotics Group develops and deploys advanced robotics in hazardous environments in order to minimize risk for the human operator.
ReNeu Robotics Laboratory
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.
PeARL
The Personal Autonomous Robotics Lab develops machine learning algorithms to solve problems that robot learners encounter in real-world interactive settings.
Socially Intelligent Machines Lab (SIMLab)
The goal of our research in the Socially Intelligent Machines (SIM) Lab is to enable robots to function in dynamic human environments by allowing them to flexibly adapt their skill set via learning interactions with end-users.
u-t autonomous Lab
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.
Advanced Robotic Technologies for Surgery Lab
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.
Autonomous Mobile Robotics Laboratory
The AMRL performs research in robotics to continually make robots more autonomous, accurate, robust, and efficient in real-world unstructured environments.