Evolving Team Behaviour for Real Robots

We report on recent work in which we employed artificial evolution to design neural network con- trollers for small, homogeneous teams of mobile autonomous robots. The robots are evolved to perform a formation movement task from ran- dom starting positions, equipped only with in- frared sensors. The dual constraints of homogene- ity and minimal sensors make this a non-trivial task. We describe the behaviour of a successful evolved team in which robots adopt and main- tain functionally distinct roles in order to achieve the task. We believe this to be the first example of the use of artificial evolution to design coordi- nated, cooperative behaviour for real robots.