Programmable Smart Membranes: Using Genetic Programming to Evolve Scalable Distributed Controllers for a Novel Self-Reconfigurable Modular Robotic Application

Self-reconFIgurable modular robotics represents a new approach to robotic hardware, in which the “robot” is composed of many simple, identical interacting modules. We propose a novel application of modular robotics: the programmable smart membrane, a device capable of actively filtering objects based on numerous measurable attributes. Creating control software for modular robotic tasks like the smart membrane is one of the central challenges to realizing their potential advantages. We use genetic programming to evolve distributed control software for a 2-dimensional smart membrane capable of distinguishing objects based on color. The evolved controllers exhibit scalability to a large number of modules and robustness to the initial configurations of the robotic filter and the particles.