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Developing a Novel Robust Multi-Agent Task Allocation Algorithm for Four-legged Robot Soccer Domain

Çetin Meriçli. Developing a Novel Robust Multi-Agent Task Allocation Algorithm for Four-legged Robot Soccer Domain. Master's Thesis, Boğaziçi University,2005.

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Abstract

Multi-robot systems become more popular since 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. Two main advantages of multi-robot systems over single robot systems are their robustness and higher performance due to parallel execution. Multi-robot systems have a wide application area from mine sweeping to planetary exploration and from soccer playing to search and rescue operations in disaster areas.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 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, it should be able to evaluate the current situation of the environment so we have to have some metrics that gives quantitative information about the environment.In this work, we first propose some metrics calculated from positions of robots and ball on the field and select a subset of these metrics that are statistically proved to be informative. Then, a task allocation algorithm is built on top of those metrics. Experimental study on both metric selection and evaluation of the designed algorithm are given.

BibTeX

@MastersThesis{cmericliMSThesis2005,
 author = {Çetin Meriçli},
 title = {Developing a Novel Robust Multi-Agent Task Allocation Algorithm for Four-legged Robot Soccer Domain},
 school = {Boğaziçi University},
 year = {2005},
 abstract = {Multi-robot systems become more popular since 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. Two main advantages of multi-robot systems over single robot systems are their robustness and higher performance due to parallel execution. Multi-robot systems have a wide application area from mine sweeping to planetary exploration and from soccer playing to search and rescue operations in disaster areas.
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 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, it should be able to evaluate the current situation of the environment so we have to have some metrics that gives quantitative information about the environment.
In this work, we first propose some metrics calculated from positions of robots and ball on the field and select a subset of these metrics that are statistically proved to be informative. Then, a task allocation algorithm is built on top of those metrics. Experimental study on both metric selection and evaluation of the designed algorithm are given.},
 bib2html_pubtype = {Thesis},
 bib2html_rescat = {Multi-robot Planning},
 bib2html_dl_pdf = {../files/cmericliMSThesis2005.pdf},
}

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