"Safe Real-World Autonomy in Uncertain and Unstructured Environments"

Zoom URL: https://ucsd.zoom.us/j/97197176606

Sylvia Herbert - UCSD


Seminar Abstract

In this talk I will present my current and future work towards enabling safe real-world autonomy. My core focus is to enable efficient and safe decision-making in complex autonomous systems, while reasoning about uncertainty in real-world environments, including those involving human interactions. These methods draw from control theory, cognitive science, and reinforcement learning, and are backed by both rigorous theory and physical testing on robotic platforms.

First I will discuss safety for complex systems in simple environments. Traditional methods for generating safety analyses and safe controllers struggle to handle realistic complex models of autonomous systems, and therefore are stuck with simplistic models that are less accurate. I have developed scalable techniques for theoretically sound safety guarantees that can reduce computation by orders of magnitude for high-dimensional systems, resulting in better safety analyses and paving the way for safety in real-world autonomy.

Next I will add in complex environments. Safety analyses depend on pre-defined assumptions that will often be wrong in practice, as real-world systems will inevitably encounter incomplete knowledge of the environment and other agents. Reasoning efficiently and safely in unstructured environments is an area where humans excel compared to current autonomous systems. Inspired by this, I have used models of human decision-making from cognitive science to develop algorithms that allow autonomous systems to navigate quickly and safely, adapt to new information, and reason over the uncertainty inherent in predicting humans and other agents. Combining these techniques brings us closer to the goal of safe real-world autonomy.


Sylvia Herbert is an Assistant Professor in Mechanical and Aerospace Engineering at the University of California San Diego. Prior to joining UCSD, she received her PhD in Electrical Engineering from UC Berkeley, where she studied with Professor Claire Tomlin on safe and efficient control of autonomous systems. Before that she earned her BS/MS at Drexel University in Mechanical Engineering. She is the recipient of the UC Berkeley Chancellor’s Fellowship, NSF GRFP, UC Berkeley Outstanding Graduate Student Instructor Award, and the Berkeley EECS Demetri Angelakos Memorial Achievement Award for Altruism.