Evolving a self -organizing neuromechanical system for self -healing aerospace structures

§NASA is developing a novel articulated truss built from a highly redundant, highly integrated network of actuators. Near -term implementations of this truss a rchitecture make use of Addressable Reconfigurable Technology (ART) and can be centrally controlled as, for example, one’s hand is directed by the central nervous system. Mid -to -far term implementations make increasing use of micro - and nano -technologies to allow truss systems to scale eventually through thousands of nodes and beyond into the realm of Super Miniaturized Addressable Reconfigurable Technology (SMART). Structures made from this material may take on shapes as required to meet mission requirem ents for deployment, storage, locomotion, shape control, and so on. One of the key applications of this technology is for nano - and pico -spacecraft. Furthermore, the large number of redundant elements opens up many possibilities to address and mitigate fa ults and failures within the truss. Not only does this architecture provide physical reconfiguration, system control must be able to adapt to its new configuration. In this work, we describe a new control architecture for a synthetic neural system design ed to meet this challenge. Genetic algorithmic evolution within supercomputer -based simulations allows the system components to situate themselves amongst each other and their environment. The synthetic neural system is based on composable behavioral uni ts called Neural Basis Functions (NBF) that provide a way to unify low -level autonomic and high -level reasoning in a single operational architecture. Distributed systems fit naturally within this framework. We describe fault modes of and recoveries enable d by the architecture and the results of our first attempts to construct a synthetic neural system based on NBFs with a focus on the self -organizing and self -healing properties of the system. We emphasize the scaling issues associated with the large number of nodes in nano -technology -based SMART structures and how distributed systems, e.g. multi -spacecraft systems, are controlled.