Abstract
Swarm robotics is an emerging research area combining swarm intelligence and robotics. Thanks to the recent achievements in optimization problem using swarm intelligence, searching problems in swarm robotics have attracted a large number of researchers. In searching problems, a swarm of robots searches for multiple targets in the environment without knowing any prior knowledge about the targets. This progress is quite similar with that of optimization problems in many aspects. Moreover, in most of the swarm robotics searching problems so far, some kinds of fitness functions are introduced for guiding the search of the swarm. This makes it a natural advantage to introduce swarm intelligence algorithms into swarm robotics. In this chapter, inspired by the fireworks algorithm, the group explosion strategy (GES) is proposed for searching multiple targets in swarm robotics. In the GES model, the whole swarm is divided into several groups. Robots in a group are spatially adjacent within the sensing range of each other. The swarm searches and collects targets in the environment without prior knowledge. Different groups do not intersect directly and their search for targets is parallel and independent. Through certain strategies, groups that run into each other will be re-arranged into new groups with possibly different members and search directions. In this way, inter-group cooperation can emerge in the swarm. The simulation results indicate that the proposed method with GES in this chapter shows great advantage against the comparison algorithm inspired from PSO.
Published Version
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