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Improving the multi-tasks distribution in multi-robot systems (Paperback)
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Improving the multi-tasks distribution in multi-robot systems (Paperback)
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This work study the coordination of multi-robot systems, in
particular, addresses the problem of the distribution of
heterogeneous multi-tasks. The main interest in these systems is to
understand how from simple rules inspired by the division of labor
in social insects, a group of robots can perform tasks in an
organized and coordinated way. We are mainly interested on truly
distributed or decentralized solutions in which the robots
themselves, autonomously and in an individual manner, select a
particular task so that all tasks are optimally distributed. In
general, to perform the multi-tasks distribution among a team of
robots, they have to synchronize their actions and exchange
information. Under this approach we can speak of multi-tasks
selection instead of multi-tasks assignment, which means, that the
agents or robots select the tasks instead of being assigned a task
by a central controller. The key element in these algorithms is the
estimation of the stimuli and the adaptive update of the
thresholds. This means that each robot performs this estimate
locally depending on the load or the number of pending tasks to be
performed.
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