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      Ant-like task allocation and recruitment in cooperative robots.

      Nature
      Algorithms, Animals, Ants, Behavior, Animal, Cooperative Behavior, Feeding Behavior, Robotics

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          Abstract

          One of the greatest challenges in robotics is to create machines that are able to interact with unpredictable environments in real time. A possible solution may be to use swarms of robots behaving in a self-organized manner, similar to workers in an ant colony. Efficient mechanisms of division of labour, in particular series-parallel operation and transfer of information among group members, are key components of the tremendous ecological success of ants. Here we show that the general principles regulating division of labour in ant colonies indeed allow the design of flexible, robust and effective robotic systems. Groups of robots using ant-inspired algorithms of decentralized control techniques foraged more efficiently and maintained higher levels of group energy than single robots. But the benefits of group living decreased in larger groups, most probably because of interference during foraging. Intriguingly, a similar relationship between group size and efficiency has been documented in social insects. Moreover, when food items were clustered, groups where robots could recruit other robots in an ant-like manner were more efficient than groups without information transfer, suggesting that group dynamics of swarms of robots may follow rules similar to those governing social insects.

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          Author and article information

          Journal
          10984052
          10.1038/35023164

          Chemistry
          Algorithms,Animals,Ants,Behavior, Animal,Cooperative Behavior,Feeding Behavior,Robotics
          Chemistry
          Algorithms, Animals, Ants, Behavior, Animal, Cooperative Behavior, Feeding Behavior, Robotics

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