Coevolution of form and function in the design of micro air vehicles

This paper discusses approaches to cooperative coevolution of for and function for autonomous vehicles, specifically evolving morphology and control for an autonomous micro air vehicle (MAV). The evolution of a sensor suite with minimal size, weight, and power requirements, and reactive strategies for collision-free navigation for the simulated MAV is described. Results are presented for several different coevolutionary approaches to evolution of form and junction (single- and multiple-species models) and for two different control architectures (a rulebase controller based on the SAMUEL learning system and a neural network controller implemented and evolved using ECkit).