Cooperative Stigmergic Navigation in a Heterogeneous Robotic Swarm

Abstract. 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 stigmergic markers 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.