Intelligent Systems in the Evolvable ANTS Architecture

Abstract

The Autonomous Nano Technology Swarm (ANTS) is a breakthrough in mission architecture that enables distributed multi-platform missions to explore autonomously multiple-faceted targets. ANTS is a biologically inspired system architecture that is adaptable, reconfigurable and evolvable in all its system hierarchies, from the swarm level down to the subsystem and component level. Both the hardware and software that constitute each layer in the ANTS architecture and their interfaces are evolvable and adaptable. Advanced autonomy is crucial in the operations of ANTS systems. We recognize the sheer computational power required by the Synthetic Neural System that is central to ANTS and have begun efforts to attain space-qualified high-performance computing capabilities. I. Introduction he Autonomous Nano Technology Swarm (ANTS) is a breakthrough in mission architecture that enables distributed multi-platform missions to explore autonomously multiple-faceted targets. These exploration missions operate in a discovery mode, so a rigid architecture with a pre-determined mission plan would not be able to respond well to unexpected findings and to exploit targets of opportunity. ANTS is a biologically inspired system architecture that is adaptable, reconfigurable and evolvable in all its system hierarchies, from the swarm level down to the subsystem and component level. Both the hardware and software that constitute each layer in the ANTS architecture and their interfaces are evolvable and adaptable. The large reconfigurable gossamer space frames are built on the same self-similar architecture as the MEMS-based reconfigurable flight electronics. A self-similar Synthetic Neural System controls each system node and the interfaces, integrating their heuristic functions and autonomic tasks. Many technology developments are required for the implementation of the ANTS architecture, including nanotechnology, advanced materials, miniaturized system components, and intelligent systems. Advanced autonomy is crucial in the operations of ANTS systems. We recognize the sheer computational power required by the Synthetic Neural System that is central to ANTS and have begun efforts to attain space-qualified high-performance computing capabilities. We are developing a validation experiment using multiple COTS Von Neumann processors for space-based Beowulf cluster in an effort funded by the NASA Space Technology 8 program. In addition, we investigate the use of Reconfigurable Data Path Processors in a non-Von Neumann architecture to increase the onboard data analysis capability and to enable in-situ knowledge discovery.