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Research Interests
My research interests lie mainly in two areas:
- high-level multi-robot coordination
- low-level robot control interfaces
My PhD work is concerned primarily with the former, but I also spend a great
deal of time on the latter.
I pursue these research interests in the
USC Robotics Lab, part of the
Center for Robotics and Embedded
Systems (CRES).
I am currently involved in 5 research projects:
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Multi-Robot Task Allocation
Important theoretical aspects of mechanisms for multi-robot task allocation
have, to date, been largely ignored. In this project, we are trying to address
part of this negligence by formally studying the problem within an
organizational framework developed in the Operations Research community. In
particular, we are currently exploring multi-robot task allocation as an
instance of the well-known Optimal Assignment Problem. In this light, we have
recently analyzed and compared the algorithmic characteristics of several
existing approaches to the problem.
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Auction-based Multi-Robot
Coordination
The key to utilizing the potential of multi-robot systems is
coordination. In this project, we are exploring economically-inspired
approaches to achieving robust multi-robot coordination. In
particular, we have developed MURDOCH, an highly-scalable,
distributed, auction-based multi-robot coordination system. A variant of the
well-known Contract Net Protocol, MURDOCH has been
experimentally validated in a variety of task domains with physical robots.
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Player / Stage
The Player/Stage project develops and distributes open-source robot control and
simulation software. The primary products of this project are Player,
a device server that provides a powerful, flexible, language- and
platform-neutral interface to a variety of sensors and actuators (e.g.,
robots); and
Stage, a highly parameterizable sensor-based multiple robot simulator.
Player & Stage are widely used in labs and classrooms around the world.
I am a founding developer on the project and I head development of Player.
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Mathematical Modeling of Multi-Agent Systems
(Led by Kristina Lerman)
Our research goals are two-fold:
- show that a distributed mechanism based on purely local interactions can
lead to the desired group behavior in several different agent-based systems;
- model and analyze these systems mathematically.
Mathematical analysis is important for several reasons: a designer of
multi-agent systems can use it to show that the proposed agent strategy leads
to the desired group behavior, find the parameters that optimize system
performance (collective behavior), and predict the global dynamics of the
system. We plan to apply this type of analysis to several software agent and
robotic systems.
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Hi-Scale User-System Interaction (HiSUSI)
(Led by Ashley Tews)
This project is concerned with investigating the high-level interaction
dynamics between people and multiple robotic and embedded systems. The
key question is how to connect possibly hundreds of users to hundreds
of systems and maintain personal interaction. An interaction
infrastructure has been developed for this purpose that allows
interaction at both extremes. This project is part of the larger Human-System
Interaction project at USC Robotics.
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