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.
We present an approach to the distributed storage of data across a swarm of mobile robots that forms a shared global memory. We assume that external storage infrastructure is absent, and that each robot is capable of devoting a quota of memory and bandwidth to distributed storage. Our approach is motivated by the insight that in many applications data is collected at the periphery of a swarm topology, but the periphery also happens to be the most dangerous location for storing data, especially in exploration missions. Our approach is designed to promote data storage in the locations in the swarm that best suit a specific feature of interest in the data, while accounting for the constantly changing topology due to individual motion. We analyze two possible features of interest: the data type and the data item position in the environment. We assess the performance of our approach in a large set of simulated experiments. The evaluation shows that our approach is capable of storing quantities of data that exceed the memory of individual robots, while maintaining near-perfect data retention in high-load conditions.
Abstract-This paper presents advances in the development of a microrobotic platform actuated by three liquid droplets in a gaseous environment (Drop-bot or Drobot). Drobot builds on the bubble robotics concept earlier introduced by Lenders [1]. A new platform design is described allowing three actuated degrees of freedom : one translational (vertical) and two rotational (tilt). The platform-supporting droplets are generated by pushing liquid out of a tank through linear actuators. Preliminary kinematic (output/input ratio), static (compliance) and dynamic (response time and evaporation time) characterizations of Drobot are reported, as well as promising experiments with an ionic liquid, whose negligible volatility is suitable for vacuum or hot environments. Additionally, a method to deduce the platform attitude from the measurement of the electrical resistance of the droplets is discussed. This work contributes toward the automatic control of the platform, which will be fully addressed in a following publication.
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