We study self-organized cooperation in a heterogeneous robotic swarm consisting of two sub-swarms.The robots of each sub-swarm play distinct roles based on their different characteristics. We investigate how the swarm as a whole can solve complex tasks through a self-organized process based on local interactions between the sub-swarms. We focus on an indoor navigation task, in which we use a swarm of wheeled robots, called foot-bots, and a swarm of flying robots that can attach to the ceiling, called eye-bots. Foot-bots have to move back and forth between a source and a target location. Eye-bots are deployed in stationary positions against the ceiling, with the goal of guiding foot-bots. We study how the combined system can find efficient paths through a cluttered environment in a distributed way. The key component of our approach is a process of mutual adaptation, in which foot-bots execute instructions given by eye-bots, and eye-bots observe the behavior of foot-bots to adapt the instructions they give. The system is based on pheromone mediated navigation of ant colonies, as eye-bots function as stigmergicmarkers for foot-bots. Through simulation, we show that the system finds feasible paths in cluttered environments, converges onto the shortest of two paths, and spreads over different paths in case of congestion. © 2010 Springer-Verlag.
CITATION STYLE
Ducatelle, F., Di Caro, G. A., & Gambardella, L. M. (2010). Cooperative stigmergic navigation in a heterogeneous robotic swarm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6226 LNAI, pp. 607–617). https://doi.org/10.1007/978-3-642-15193-4_57
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