Collision-Induced “Priority Rule” Governs Efficiency of Pheromone-Communicating Swarm Robots

  • Ryusuke Fujisawa
  • Shigeto Dobata
  • Yuuta Sasaki
  • Riku Takisawa
  • Fumitoshi Matsuno
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7461)


The recruiting system in foraging ant colonies is a typical example of swarm intelligence. The system is underpinned by the use of volatile pheromones which form a trail connecting from nest to food. We have incorporated this property into the behavior of the swarm of real robots. Because the trail is narrow, avoiding overcrowding on the trail, as well as in the environment, is a critical issue in maintaining efficiency of the swarm behavior. In this paper, we studied how “priority rule,h a behavioral rule under which a robot is given priority over the other robot in collision, affect the group-foraging performance of pheromone-mediated swarm robots. Using real robot experiments, we found that the alteration in the priority rules can have substantial effects on the group-foraging performance. Our results highlight the importance of implementing “fine-tuningh algorithms to improve the performance of complex swarm systems.


Swarm Intelligence Priority Rule Pheromone Trail Swarm Size Reaction Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ryusuke Fujisawa
    • 1
  • Shigeto Dobata
    • 2
  • Yuuta Sasaki
    • 1
  • Riku Takisawa
    • 1
  • Fumitoshi Matsuno
    • 3
  1. 1.Hachinohe Institute of TechnologyAomoriJapan
  2. 2.University of the RyukyusOkinawaJapan
  3. 3.Kyoto UniversityKyotoJapan

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