Abstract
The work presented in this paper approaches autonomous implementation from a different perspective than that used for traditional NASA applications, i.e. for robotics and rovers. Autonomous operations are vital capabilities and critical technologies required for the success, safety and crew survival of NASA deep space missions beyond LEO. This is relevant since NASA is implementing the President's Space Policy Directive, and a key objective is sustainable space exploration with reusable spacecraft and architecture, which could later take humans to Mars. This capability will require not only autonomous operations of spacecrafts, but also of systems that will be needed for habitation on the Moon and Mars. The future of “true” autonomous systems requires independent thinking and reasoning to eliminate the need for persistent updates and oversight by humans. Autonomous operations are also important for enabling passive monitoring of the progress of a task when desirable, to enable system awareness for rapid comprehension and action by operators. Because of the complexity of these systems, an architecture that accommodates multiple autonomous systems hierarchically organized, so that systems at higher levels have authority to manage systems at lower levels is required; this hierarchical authority is particularly important when considering decisions made at a lower level can affect the higher-level systems. The paper will describe a software platform called the NASA Platform for Autonomous Systems (NPAS), along with processes that facilitate implementing hierarchical distributed autonomy. NPAS enables implementation of “thinking” autonomy, whereby model-based analysis is achieved on-board by the autonomous system application. This is in contrast with typical autonomous systems or Brute-Force Autonomy (BFA) strategies that consists of considering all possible cases for autonomous decisions, and applying those specific strategies to generate solutions offline. In BFA, these cases and solutions are then incorporated in the processor for implementing autonomy, and the processor simply chooses the decisions which correspond to each prescribed case. An interpretation of this methodology suggests that the “thinking” is done offline by experts. NPAS is a platform that integrates all functions required for autonomy: (1) Integrated System Health Management (ISHM); (2) autonomy strategies, guided by system health and concepts of operations; (3) domain objects (system elements) and infrastructure to create complete application domain knowledge models (4) infrastructure to create, schedule, and execute mission plans; (5) infrastructure to develop user interfaces for comprehensive awareness; and (6) infrastructure to integrate distributed autonomous applications across networks. The paper will also discuss how NPAS has been used to enable autonomy, and how these capabilities could be leveraged and used to implement autonomy for Gateway. Demonstration results from specific NPAS prototype applications will be described, that demonstrates distributed hierarchical autonomy for a space habitat mockup built by Northrop Grumman Innovation Systems (NGIS).
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