  Swarm foraging is a common test case application for multi-robot systems. In
this paper we present a novel algorithm for controlling swarm robots with
limited communication range and storage capacity to efficiently search for and
retrieve targets within an unknown environment. In our approach, robots search
using random walk and adjust their turn probability based on attraction and
repulsion signals they sense from other robots. We compared our algorithm with
five different variations reflecting absence or presence of attractive and/or
repulsive communication signals. Our results show that best performance is
achieved when both signals are used by robots for communication. Furthermore,
we show through hardware experiments how the communication model we used in the
simulation could be realized on real robots.
