Get in touch: cooperative decision making based on robot-to-robot collisions

  • Authors:

  • Thomas Schmickl;Ronald Thenius;Christoph Moeslinger;Gerald Radspieler;Serge Kernbach;Marc Szymanski;Karl Crailsheim

  • Affiliations:

  • Department for Zoology, Karl-Franzens-University Graz, Graz, Austria;Department for Zoology, Karl-Franzens-University Graz, Graz, Austria;University of Applied Sciences St. Poelten, St. Poelten, Austria;Department for Zoology, Karl-Franzens-University Graz, Graz, Austria;Institute of Parallel and Distributed Systems, University of Stuttgart, Stuttgart, Germany;Institute for Process Control and Robotics, University Karlsruhe (TH), Karlsruhe, Germany;Department for Zoology, Karl-Franzens-University Graz, Graz, Austria

  • Venue:
  • Autonomous Agents and Multi-Agent Systems
  • Year:
  • 2009

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Abstract

We demonstrate the ability of a swarm of autonomous micro-robots to perform collective decision making in a dynamic environment. This decision making is an emergent property of decentralized self-organization, which results from executing a very simple bio-inspired algorithm. This algorithm allows the robotic swarm to choose from several distinct light sources in the environment and to aggregate in the area with the highest illuminance. Interestingly, these decisions are formed by the collective, although no information is exchanged by the robots. The only communicative act is the detection of robot-to-robot encounters. We studied the performance of the robotic swarm under four environmental conditions and investigated the dynamics of the aggregation behaviour as well as the flexibility and the robustness of the solutions. In summary, we can report that the tested robotic swarm showed two main characteristic features of swarm systems: it behaved flexible and the achieved solutions were very robust. This was achieved with limited individual sensor abilities and with low computational effort on each single robot in the swarm.