Autonomous systems comprise of intelligent machines, devices, and software that are aware of and interact with their environment, making independent decisions and learning in the real-world. These systems will soon be able to replace humans in hazardous environments and tedious jobs, provide them with up-to-the-minute situational awareness, assist them in difficult or repetitive tasks, and enhance their capabilities.
Our research focuses on the design of autonomous systems that can seamlessly infer, reason, and act in the real-world using large amounts of data, learn from their experiences and improve their performance, accept naturally expressed instruction from humans, adapt and respond to unpredictable situations, and effectively interact with each other and humans to accomplish collaborative tasks. To realize this research, we develop new methods drawing from control theory, optimization, and learning and AI as well as the necessary theoretical and experimental support. Our application domains include robotics, cyber-physical systems, and healthcare/medicine.