A team of relatively simple robots may achieve a complex goal more
effectively than a single complex robot if a proper design paradigm
is used. Multirobot systems have a wide application area from
search and rescue operations in disaster areas and planetary
exploration to soccer playing. Robot soccer is a good platform to
test and develop multi-robot applications because it has some
physical limitations such as limited and noisy sensorial
information and noisy actuators as in the real life and it also has
a highly dynamic environment. The ultimate goal of winning the game
should be decomposed into a sequence of sub-goals and proper
sequences of actions for achieving the subgoals should be selected
and refined through execution. In order to be able to select proper
actions at a time, the system should be able to evaluate the
current state therefore some metrics that gives quantitative
information about the environment are needed. This book presents a
set of metrics calculated from positions of robots and ball on the
field, and a statistical method for evaluating their usefulness. A
task allocation algorithm built on top of those metrics is also
presented.
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