Layered T&E for Safety-Critical Autonomous Systems

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The overall goal of this project is to develop a layered safety-critical framework for test and evaluation (T&E) with a focus on (semi-) autonomous systems. We leverage the structure of layered architectures to design tests that evaluate the safety-critical nature of next generation systems, specifically the multiple time scales present in modern day systems: the planning layer (minutes), the trajectory generation layer (seconds), and the real-time control layer (milliseconds). We exploit models present at these different levels, and the interactions between the layers, to design tests that evaluate system specifications in a provably safe manner. This will be achieved through the use of safety filters around autonomy features —- including AI driven controllers —- the guarantee safe T&E. Additionally, we exploit the layered layered structure of software for autonomous systems to allow for computationally efficient approaches to T&E that facilitate the integration of data-driven methods in uncertain environments. The methods developed are being deployed experimentally on a wide-variety of robotic systems: from legged robots, to flying robots, to multi-robot systems with legged and flying robots.

Current participants:

Additional participants:


Past participants:



My groups goals under this project are focused on the following objectives:

  • Data-driven T&E: Exploitation of data logging and data-in-the-loop testing in conjunction with the layered architecture to validate simulation- and regression-based elements of the certification process.
  • Compositional T&E: Development of compositional approaches to T&E allowing a smaller number of more comprehensive tests to validate system specifications.


Research supported by the AFOSR Test and Evaluation program, grant FA9550-22-1-0333

  • Agency: AFOSR
  • Grant number: FA9550-22-1-0333
  • Start date: 30 Sep 2022
  • End date: 29 Sep 2025
  • Support: 1 postdoc, 1-2 graduate students
  • Reporting: Annual program review + report