Hybrid Control of Swarms for Resource Selection

  • Marco TrabattoniEmail author
  • Gabriele Valentini
  • Marco Dorigo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11172)


The design and control of swarm robotics systems generally relies on either a fully self-organizing approach or a completely centralized one. Self-organization is leveraged to obtain systems that are scalable, flexible and fault-tolerant at the cost of reduced controllability and performance. Centralized systems, instead, are easier to design and generally perform better than self-organizing ones but come with the risks associated with a single point of failure. We investigate a hybrid approach to the control of robot swarms in which a part of the swarm acts as a control entity, estimating global information, to influence the remaining robots in the swarm and increase performance. We investigate this concept by implementing a consensus achievement system tasked with choosing the best of two resource locations. We show (i) how estimating and leveraging global information impacts the decision-making process and (ii) how the proposed hybrid approach improves performance over a fully self-organizing approach.



Gabriele Valentini acknowledges support from the NSF grant No. PHY-1505048. Marco Dorigo acknowledges support from the Belgian F.R.S.-FNRS, of which he is a Research Director. The work presented in this paper was partially supported by the FLAG-ERA project RoboCom++ and by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement number 681872).


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.IRIDIAUniversité Libre de BruxellesBrusselsBelgium
  2. 2.School of Earth and Space ExplorationArizona State UniversityTempeUSA

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