Interaction of robot swarms using the honeybee-inspired control algorithm BEECLUST
In this work we investigated how robust a robot swarm acts against disturbances caused by another robot swarm, both using the BEECLUST algorithm, which is inspired by honeybee behaviour. For our investigation we simulated an environment with an ambient illuminance, a light spot and a shadow spot. In such an environment we tested two different castes of Jasmine III robots whereas each caste had to perform a different task. One swarm aggregates at places of high illuminance (light spot) and the other one at places of low illuminance (shadow spot). We show that small swarm populations can benefit from the presence of another robot swarm. Medium populated swarms are affected neither positively nor negatively. Large swarm populations act robust against disturbances caused by other robot swarms as long as no jamming effects occur. In this article we show that the BEECLUST algorithm provides all features for making collective decisions. Furthermore we show that the robustness of the BEECLUST algorithm allows us to control a heterogeneous robot swarm in environments which demand differing controller strategies and swarm intelligent behaviour.
collective decision swarm intelligent swarm robotics