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SDCPS: Symbiotic Design for Cyber Physical Systems

 

Program Summary

Cyber physical systems (CPS) are instrumental to current and future Department of Defense (DoD) mission needs – unmanned vehicles, weapon systems, and mission platforms are all examples of military-relevant CPS. These systems and platforms integrate cyber and physical subsystems, and the enormous complexity of the resulting CPS has made their engineering design a daunting challenge. An immediate consequence of this complexity is development cycles with prolonged timelines that challenge DoD’s ability to counter emerging threats.

CPS design is a complex endeavor that involves many domains – from cyber (e.g., software, control, computing, and communication) to physical (e.g., structural, mechanical, thermal, etc.) to manufacturing – and upwards of hundreds of domain-specific tools orchestrated by large teams of engineers with extensive domain knowledge and subject matter expertise. Current engineering design processes start with requirements-driven decomposition into discipline-specific design flows that, at their core, are concurrently running sequential decision-making processes that involve generating candidate architectures; evaluating, selecting, and refining options; and integrating the design until requirements are satisfied.

The goal of the Symbiotic Design for CPS (SDCPS) program is to develop AI-based approaches to enable correct-by-construction design of military-relevant CPS. SDCPS seeks to reduce the time from CPS inception to deployment from years to months, and enhance innovation in design. To accomplish this, SDCPS will address the following three intrinsic challenges:

  1. Predictability – The soundness of design decisions relies on accurate predictions of performance prior to the implementation of software and physical components. However, accurate predictions require high-fidelity models that are cost- and time-prohibitive to produce. Cost-effective modeling processes produce results with substantial uncertainty.
  2. Convergence – Design teams are federated according to discipline boundaries. However, separation of concerns within a complex system neglects the interdependence of design decisions, rendering rapid convergence to a viable integrated solution practically impossible.
  3. Exploration – Limited by time and resources, engineers have to make tradeoffs that constrain the exploration of the design space to the familiar and known-feasible. This leaves vast areas of design space unexplored, which may contain unconventional but highly performant solutions.

The vision of the program is to vastly expand coverage and accelerate exploration of CPS design spaces with the symbiosis of two very different kinds of agents: humans with their uncanny ability to create intuitive associations across design domains, and machines with their ability to recognize statistical patterns from data and navigate vast search spaces for optimal solutions. The program aims to realize this vision by transforming the human-focused model-based design flows used today into a symbiotic process of collaborative discovery by humans and continuously learning AI-based co-designers.

For more information, please see the Symbiotic Design for Cyber Physical Systems Proposers Day Announcement and the Symbiotic Design for Cyber Physical Systems BAA.

 

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