Summary
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Although navigation for single robot systems has been studied intensively
in the past, the problem of coordinating teams of mobile robots is virtually
unexplored. One of the reasons is that the complexity of state estimation and
planning problems generally increases exponentially in the number of robots,
because one always has to consider the composite state space. On the other
hand, the use of multiple robots is often suggested to gain advantages over
single robot systems. Cooperating robots have the potential to accomplish
single tasks faster than single robots. Additionally, teams of robots can be
expected to be more fault-tolerant than a single possibly expensive robot.
In this project we will investigate the problem of coordinating the actions
of a team of mobile robots while they are exploring their environment. The
key problem in multi-robot exploration is to choose different actions for
the individual robots so that they simultaneously explore different areas
of their environment. Since exploration is a dynamic process in which the
robots acquire knowledge about their environment, the overall coordination
task is a prototypical problem of spatial cognition. Throughout this project
we will investigate different aspects of coordinating a team of mobile robots
that explores its environment. In the first phase, we will consider appropriate
spatial representations of the environment, improved targetpoint selection
techniques, and decision-theoretic techniques for action selection under different
situations of uncertainty. The long-term goal of this project is the development
of an integrated technique for multi-robot navigation including multirobot
exploration, multi-robot map registration as well as the maintenance of models
by multi-robot systems acting in a dynamic environment.
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