From Natural to Artificial Swarm Intelligence
From Natural to Artificial Swarm Intelligence
Ant Colony Optimization
Guiding robots' behaviors using pheromone communication
Autonomous Robots
Dependency by Concentration of Pheromone Trail for Multiple Robots
ANTS '08 Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence
The Superorganism: The Beauty, Elegance, and Strangeness of Insect Societies
The Superorganism: The Beauty, Elegance, and Strangeness of Insect Societies
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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.