Evolving robot controllers for a homogeneous robotic swarm

Abstract

A homogeneous robotic swarm has a great potential to achieve a highly complex task that cannot be solved by a single robot. However, it would not be so easy to develop an appropriate collective behavior because of the intrinsic large redundancy in itself. In this paper, a robot controller is designed with an evolving artificial recurrent neural network (EANN) to develop coordinated collective behavior autonomously. However, it is well-known that an EANN shows the performance strongly dependent on its topological structure. In addition to this, no general guidelines have been known to the question of how to design an appropriate topological structure of an EANN. Therefore, as the beginning of solving this question, an approach to giving the evolvability of the topological structure at the limited part between the hidden layer and the output layer is introduced. A series of computer simulations are conducted to draw a conclusion.