Segregating multiple groups of heterogeneous units in robot swarms using abstractions

This paper addresses the problem of segregation of groups of heterogeneous units in robot swarms. We propose a controller that can drive robots in a way that each group composed of robots of a similar type will form clusters while maintaining segregation from other groups. The approach is based on abstractions created to represent each group of robots and an artificial potential function used to segregate the groups. Different from previous works on swarm segregation, we can mathematically guarantee that by using our approach the system will always converge to a state where multiple dissimilar groups are segregated. Moreover, in some situations, our controller does not require all robots to have information about all the other robots in the system. We demonstrate the effectiveness of our controller with simulations with different types of robots and varying number of robots and groups.