This article is centred on the application of evolutionary techniques to the automatic design of neural controllers for mobile robots. About 30 papers are reviewed and classified in a framework that takes into account the specific robots involved, the behaviors that are evolved, the characteristics of the corresponding neural controllers, how these controllers are genetically encoded, and whether or not an individual learning process complements evolution. Related research efforts in evolutionary robotics are occasionally cited. Foreseeable bottlenecks and prospects of improvement are discussed.