A number of leading robotics researchers (including for
instance, Brooks, Beer and Arkin), tell us their work was
inspired in part by the behavior of insects.
Recently, ants have captured the imagination of computer
science and network systems researchers as an inspiration
for their optimizing algorithms (Bonabeau).
In the
MultiRobot Lab we are particularly interested in learning
about social insects, as they provide an existence
proof of successful large-scale robust behavior forged from
the interaction of many, simple agents.
Ant behavior can offer a wealth of ideas on how to organize
a cooperating colony of agents. As an example, even though
they are only capable of very short range communication,
ants are able to carry out complex scouting and retrieval
operations over tens of meters. The techniques social
insects utilize for staging such complex operations could
also be employed in the design of robust multi-robot systems
--- it is important for us to learn what insects have to
offer.
Biologists are also beginning to draw on computer science. In a
recent Nature article, for instance, Deborah Gordon
suggested that the growth of theory in social insect research
has been inspired by the artificial intelligence community.
Accordingly, we believe the research in our lab can contribute
substantially to the study of insect behavior; in particular, we
have developed
- Vision-based tracking software that can provide
accurate, real-time information about the movements of
animals being observed.
- Modeling tools able to infer the behavior of the
agents being tracked.
- Theoretical metrics of social diversity and
agent difference that can be used in the analysis of social
insect behavior.
We will extend these existing tools for the observation of insects
in our laboratory.
We will also develop new tools for modeling groups at a
societal level rather than just the individuals in a society.
