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Efficient collaboration for
mobile robotic networks in dynamic environments
Abstract: In
this talk, we will address the following class of multi-agent
problems. Consider a geographical region, in which a certain
stochastic process generates spatially localized "tasks." Tasks
can represent, for example, pick- up and/or delivery of goods,
data packets generated by mobile user terminals, or on-site
investigation of events of interest. In a biological setting, a
taks might represent the availability of a food
item, or other scarce resource. A number of mobile agents are
able to complete these task by moving to the corresponding
location. It is desired to minimize the average delay in task
completion, or some other measure of quality of service.
The underlying mathematical problem in many of these
applications can be studied within the framework of spatial
queues, in which service the tasks as customers and the mobile
agents as servers. Cooperation between agents occurs as workload
sharing. Control policies have to typically address two key
challenges: task allocation among the agents and service
schedule for each agent. In general, these two features are
highly coupled and, therefore, devising an optimal or, at least,
a provably efficient policy is an extremely difficult problem.
Considering motion constraints for the agents, as should be done
for Unmanned Aerial Vehicles (UAVs), complicates things further.
A natural way to reduce the complexity is to partition the
workspace among the agents and then let each agent follow a
certain set of rules in its own region. To which extent does
this decoupling strategy affect optimality? How can agents
compute a partition of the workspace in the absence of a central
authority, and with limited communication abilities? We
will consider a number of scenarios, in which different
partitions arise in optimal policies. In addition, we will
illustrate novel phase transition phenomena induced by the
agents' dynamics.
Papers:
Paper1,
Paper2.
Biography:
Emilio
Frazzoli is an Associate Professor of
Aeronautics and Astronautics
with the
Laboratory for Information and Decision
Systems at the
Massachusetts Institute of Technology
. He received a Laurea degree in
Aerospace Engineering
from the University of Rome,
"Sapienza"
, Italy, in 1994, and a Ph. D. degree in Navigation and Control
Systems from the Department of Aeronautics and Astronautics of
the Massachusetts Institute of Technology, in 2001. Between 1994
and 1997 he worked as an officer in the
Italian Navy,
and as a spacecraft dynamics specialist for the European Space
Agency Operations Centre (ESOC)
in Darmstadt, Germany, and
Telespazio,
in Rome, Italy. From 2001 to 2004 he was an Assistant Professor
of Aerospace Engineering at the University of Illinois at
Urbana-Champaign. From 2004 to 2006 he was an Assistant
Professor of Mechanical and Aerospace Engineering at the
University of California, Los Angeles. He is a Senior Member of
the American Institute of Aeronautics and Astronautics and of
the Institute for Electrical and Electronics Engineers. He was
the recipient of a NSF CAREER award in 2002.
Dr. Frazzoli's
current research interests include algorithmic, computational
and geometric methods for the design of complex control systems,
in aerospace and other domains. Application areas include
distributed cooperative control of multiple-vehicle systems,
guidance and control of agile vehicles, mobile robotics,
high-confidence embedded systems.
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