We are pursuing a research program focused on studying, synthesizing, and analyzing robot group behavior and learning. The goal of the research is to understand the types of simple local interactions which produce complex and purposive group behaviors, both in nature and in synthetic systems. We have developed a bottom-up, behavior-based approach that can be used to structure and simplify the process of both designing and analyzing emergent group behaviors. The approach utilizes a biologically-inspired notion of basis behaviors for control, both at the individual and collective level.
Based on the notion of using a small set of composable behaviors as a substrate for control and representation, we have also developed methods for single and multi-robot learning. Our current research focuses on methods for developing adaptive multi-robot controllers for both loosely-coupled and tightly-coupled task domains. We are currently pursuing the following projects:
controller architectures and performance:
biologically inspired models:
interaction with non-robotic systems:
For details, see our projects page and the Interaction Lab home page.
For relevant publications, please see Maja's publications page and the Interaction Lab publications page.
Go to the Interaction Lab home page.