Evolution of Neuro-Controllers for Robots’Alignment using Local Communication

In this paper, we use artificial evolution to design homogeneous neural network controller for groups ofrobots required to align. Aligning refers to the process by which the robots managed to head towards a commonarbitrary and autonomously chosen direction starting from initial randomly chosen orientations. The cooperativeinteractions among robots require local communications that are physically implemented using infraredsignalling. We study the performance of the evolved controllers, both in simulation and in reality for differentgroup sizes. In addition, we analyze the most successful communication strategy developed using artificialevolution