Anytime coevolution of form and function

This paper describes an approach to continuous coevolution of form (the morphology) and function (the control behaviour) for autonomous vehicles. This study focuses on coevolution of the characteristics such as beam width and range of individual sensors in the sensor suite, and the reactive strategies for collision-free navigation for an autonomous micro air vehicle. The results of the evolution of the system in a fixed simulation model were compared to case-based anytime learning (also called continuous and embedded learning) where the simulation model was updated over time to better match changes in the environment.