Abstract
A solution for a class of multi-robot task allocation problems is presented in this work. The basic problem requires that the robots from a team gather randomly spread samples from an environment and deposit them to a storage facility. We focus on a finite-state (discrete) formulation, where the environment is abstracted to a weighted graph, and clusters of samples randomly appear in the nodes of this graph. Under the assumption that a central unit that communicate with all robots exists, we derive algorithmic solutions that simultaneously run on (and exchange information between) the central unit and individual robots. Although these algorithms are derived for a problem with specific assumptions, we include ideas for adjusting the solution for related problems belonging to the same class.
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