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Autonomy and Complexity at Sandia Executive Summary of Academic Alliance Workshop on Autonomy and Complex Systems.

Sandia has identified autonomy as a strategic initiative and an important area for providing national leadership. A key question is, “How might autonomy change how we think about the national security challenges we address and the kinds of solutions we deliver?” Three workshops at Sandia early in 2017 brought together internal stakeholders and potential academic partners in autonomy to address this question. The first focused on programmatic applications and needs. The second explored existing internal capabilities and research and development needs. This report summarizes the outcome of the third workshop, held March 3, 2017 in Albuquerque, NM, which engaged Academic Alliance partners in autonomy efforts at Sandia by discussing research needs and synergistic areas of interest within the complex systems and system modeling domains, and identifying opportunities for partnering on laboratory directed and other joint research opportunities.

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Autonomy for Hypersonics Mission Campaign (A4H)

A4H is developing autonomous hypersonic flight vehicles that can intelligently navigate, guide, and control themselves and home-in on targets. Autonomous systems are characterized by the use of closed-loop SENSE-THINK-ACT operations to achieve their desired goals. Closing the SENSE-THINK-ACT loop onboard these systems will provide an improved ability to engage diverse targets in contested environments.

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Synthesis of Correct Digital Controller Models from Specifications by Model Transformation (21-0320)

The design of high consequence controllers (in weapons systems, autonomy, etc.) that do what they are supposed to do is a significant challenge. Testing simply does not come close to meeting the requirements for assurance. Today circuit designers at Sandia (and elsewhere) typically capture the core behavior of their components using state models in tools such as STATEFLOW. They then check that their models meet certain requirements (e.g. “The system bus must not deadlock” or “both traffic lights at an intersection must not be green at the same time”) using tools called model checkers. If the model checker returns “yes” then the property is guaranteed to be satisfied by the model. However, there are several drawbacks to this industry practice: (1) there is a lot of detail to get right, this is particularly challenging when there are multiple components requiring complex coordination (2) any errors returned by the model checker have to be traced back through the design and fixed, necessitating rework, (3) there are severe scalability problems with this approach, particularly when dealing with concurrency. All this places high demands on the designers who now face not only an accelerated schedule but also controllers of increasing complexity. This report describes a new and fundamentally different approach to the construction of safety-critical digital controllers. Instead of directly constructing a complete model and then trying to verify it, the designer can start with an initial abstract (think “sketch”) model plus the requirements, from which a correct concrete model is automatically synthesized. There is no need for post-hoc verification of required functional properties. Having tool to carry this out will significantly impact the nation’s ability to ensure the safety of high-consequence digital systems. The approach has been implemented in a prototype tool, along with a suite of examples, including ones that reflect actual problems faced by designers. Our approach operates on a variant of Statecharts developed at Sandia called Qspecs. Statecharts are a widely used formalism for developing concurrent reactive systems, supporting scalability through allowing state models containing composite states, which are the serial or parallel composition of substates which can themselves contain statecharts. Statecharts enable an incremental style of development, in which states are progressively refined to incorporate greater detail in an incremental model of software development. Our approach formulates a set of constraints from the structure of the models and the requirements and propagates these constraints to a fixpoint. The solution to the constraints is an inductive invariant along with guards on the transitions. We also show how our approach extends to implementation refinement, decomposition, composition, and elaboration. We currently handle safety requirements written in LTL (Linear Temporal Logic)

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