Research interests summary for Naomi Ehrich Leonard
Leonard specializes in a branch of engineering and applied mathematics called control theory.
The field involves designing and analyzing methods for influencing the behavior of complex,
dynamical systems using feedback. Feedback refers to adjustments in actions taken by a system
in response to measurements of the systemÕs own state; feedback is critical for performance and
robustness in self-regulating engineered systems and, for the very same reasons, feedback is
ubiquitous in biological systems at every scale.
In recent years, Leonard has been interested in coordinated control of mobile, multi-agent
systems in engineering (robotic teams) and in nature (animal groups). A central goal is using
formal analysis to understand and to derive the systematic and automatic means for collective
motion, collective sensing and collective decision-making from the responsive behavior of
individual agents to their environment and to the behavior of other agents in the group.
She applies this research to a new kind of automated and adaptive ocean observing system that
consists of a coordinated network of underwater robotic vehicles that carry sensors to collect
scientific data in the ocean; this work has exciting implications for contributing to a better
understanding of our changing environment. She co-leads a large, collaborative effort called
Adaptive Sampling and Prediction that featured a major field experiment in Monterey Bay,
California in August 2006 and built off an earlier major field experiment also in Monterey Bay
in August 2003.
Using similar mathematical concepts and tools from control theory, Leonard collaborates with
biologists to study fish schooling, seeking to help understand the coupled roles of feedback,
information flow and spatial dynamics in collective behavior and decision-making in the school.
She is interested in the joint challenge to explain the enabling mechanisms in animal groups
and to define provable mechanisms for robotic groups. Her approach with her collaborators is
an integrated one: formal bio-inspired models and analysis tools derived to synthesize collective
robotic behavior can be used to evaluate design hypotheses for animal groups; subsequent
revelations from the biology will in turn inspire new strategies for robotic systems.
Leonard also works in collaboration with engineers, applied mathematicians, and cognitive and
social psychologists to investigate decision dynamics in mixed teams of humans and robots,
exploring how humans and robots can best jointly contribute to complex decision-making problems.