Evolving Computers from Tools to Partners in Cyber-Physical System Design

Department of Defense (DOD) systems and platforms are composed of numerous integrated cyber-physical subsystems, which create an enormous amount of complexity and makes their engineering a daunting task. Today, designing cyber-physical systems (CPS) requires an army of skilled engineers with the right domain expertise, and hundreds of domain-specific tools. The process used to design these systems is largely manual, creating long design cycles that often result in costly redesigns after building and testing the systems. The flaws in the process are numerous – from balancing predictability with cost-efficiency to operating under tight time constraints to integrating disparate pieces from multiple design teams. Further, teams are often limited to focusing on known design approaches, restricting their ability to create or identify more sophisticated system alternatives or innovative concepts.

“Current approaches to designing cyber-physical systems are largely manual, costly, and inefficient, sometimes taking decades to complete,” said Dr. Sandeep Neema, a program manager in DARPA’s Information Innovation Office (I2O). “Within the defense community, there is increased demand for mission-specific system design that could be stood up quickly. Similarly, updating and advancing large legacy platforms remains a challenge. To support the rapidly evolving defense landscape, we need a way of accelerating and streamlining CPS design – one that could take advantage of new machine learning and automation capabilities.”

DARPA created the Symbiotic Design for Cyber Physical Systems (Symbiotic Design) program to bring intelligent automation into the CPS design process. The program will explore fusing model-based design with machine reasoning and learning to develop a core set of AI-enabled tools that designers can use to accelerate the process from design concept to developed system. The tools will support the search, composition, evaluation, and exploration of knowledge bases and design corpora, and will come together to form an AI-enabled co-designer that provides its human counterparts with a true design partner.

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