We present a decentralized and scalable approach for deployment of a robot swarm. Our approach tackles scenarios in which the swarm must reach multiple spatially distributed targets, and enforce the constraint that the robot network cannot be split. The basic idea behind our work is to construct a logical tree topology over the physical network formed by the robots. The logical tree acts as a backbone used by robots to enforce connectivity constraints. We study and compare two algorithms to form the logical tree: outwards and inwards. These algorithms differ in the order in which the robots join the tree: the outwards algorithm starts at the tree root and grows towards the targets, while the inwards algorithm proceeds in the opposite manner. Both algorithms perform periodic reconfiguration, to prevent suboptimal topologies from halting the growth of the tree. Our contributions are (i) The formulation of the two algorithms; (ii) A comparison of the algorithms in extensive physics-based simulations; (iii) A validation of our findings through real-robot experiments. reach a number of distant locations. While navigating to these locations, the robots must spread without splitting the network topology in disconnected components. The robots must achieve a final configuration in which data can flow between any two target locations, using the robots as relays.It is important to notice that it is not required for all of the robots to take part in the final topology. Rather, it is desirable that as few robots as possible are engaged in connectivity maintenance, as this would free any extra robot for others tasks or to act as occasional replacement for damaged robot in the topology. In contrast, the robots that are part of the final topology must form a persistent communication backbone that can be used by any robot when necessary.
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