My research focuses on learning representations in order to enable effective human-robot teaming. Specifically, I’m interested in learning useful representations of the complicated structure of multi-robot systems, representations that enable more effective control of multi-robot systems, and representations that enable robots to work directly alongside humans.

See my submitted and accepted publications below.

Representations for Multi-Robot Structure

Multi-robot systems are complex, involving many different forms of relationships connecting individual robots. As these systems grow in size it can become extremely difficult to display their state to a human teammate or for a human teammate to understand the roles of individual robots. I’m interested in learning representations that make it easier for a teammate to understand the structure of a multi-robot system - for example, embedding multiple relationship graphs into a unified vector representation of each robot to use as input for machine learning algorithms like clustering, or graph representation learning to create an approximation of the known relationships.

Representations for Multi-Robot Control

The complexities that make multi-robot systems difficult to understand also make them difficult for human operators to control. My research develops representations that make multi-robot systems easier to control, such as learning optimal weights that determine without a human operator how leader robots should behave to effectively lead followers or how robots should adapt to team composition changes. Representations for control can also take the form of representing interactions between robots as games to enable communication-free navigation or fusing sensor observations from multiple robots to identify the most informative views.

Representations for Human-Robot Teaming

Finally, I’m interested in ultimately enabling robots to more capably work as teammates with humans. This begins with representing, recognizing, and analyzing the activities of humans. I’ve also worked with enabling a robot teammate to recognize the intent of a team of humans, and hope to work with human teammates alongside multiple robots in the future.

Submitted Papers

Accepted Papers