Developing a novel robust multi-agent task allocation algorithm for four-legged robot soccer domain

Abstract

Multi-robot systems become more popular since a team of relatively simple robotsmay achieve a complex goal more effectively than a single complex robot if a properdesign paradigm is used. Two main advantages of multi-robot systems over singlerobot systems are their robustness and higher performance due to parallel execution.Multi-robot systems have a wide application area from mine sweeping to planetaryexploration and from soccer playing to search and rescue operations in disaster areas.Robot soccer is a good platform to test and develop multi-robot applicationsbecause it has some physical limitations such as limited and noisy sensorial informationand 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, itshould be able to evaluate the current situation of the environment so we have to havesome 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 provedto 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 algorithmare given.