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On different communication modalities between foraging robot swarms

par Miletitch, Roman
Président du jury Bersini, Hugues
Promoteur Dorigo, Marco
Co-Promoteur Trianni, Vito
Publication Non publié, 2024-01-29

Thèse de doctorat

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Résumé :

Coordination in a group relies heavily on the type and quality of interactions and communication among individuals. In swarm robotics, communication can make the difference between a heap of isolated robots working independently of each other, and a connected swarm displaying self-organisation. Communication between robots in a swarm can be indirect, for instance through stigmergy whereby robots exploit the sign of previous actions to coordinate, or direct, by means of messages exchanged among robots for the purpose of influencing each other's behaviour. In the latter case, messages can consist either of simple signals, or more structured information, possibly encoding some concept representing features of the environment or of the desired coordination outcome. More complex communication can support more complex self-organising behaviors, deeply impacting on how the swarm tackles the task at hand. In this work, we consider different ways of exploiting communication in the context of a foraging task, in which robots search an open environment for resources to be exploited. Foraging requires abilities such as navigation, exploration and collective decision making. Coordination within a foraging context can lead to higher efficiency in exploiting resources, both in the short or in the long run, by avoiding over-exploitation. Throughout my thesis, foraging is used as a means to study the coupling between different communication processes and the undertaking of a meaningful task by the robots. Specifically, we study three different uses of communication during foraging. Firstly, we focus on simple aggregation of information, and study three parameter-free information processing mechanisms. These result in varying behavior, from the selection of a single resource by the whole swarm to the robots splitting among the resources present. This study is supported by an extensive analysis of navigation and congestion, helping to explain how swarm density can affect the perceived quality of a resource.Next, we consider an exchange of more complex signals, inspired by the honeybeevalue-sensitive decision making abilities. This results in a fine-grained load-balancing between resources, suitable for an adaptive exploitation of sources at the collective level, without requiring individuals to compare the profitability of different sources or a central planner with global knowledge of the environmental conditions. Last, we tackle the case of robots talking about the resources, that is, assigning names to resources following dynamics typical of language evolution. Such a process initially leads to a temporary segregation of vocabulary, closely tied to the swarm's topology. However, over time, the swarm converged to a comprehensive and accurate description of its surroundings, encompassing all relevant resources. The emergent naming conventions facilitated effective coordination and decision-making within the swarm, highlighting the potential of language dynamics in enhancing collective behavior in complex environments.