Analysis techniques of autonomy framework metrics for autonomous developers

George J. Hwang; Aniruddha Katre; Kyle M. Hart; Charles A. Rea

doi:10.1117/12.2623376

6 June 2022 Analysis techniques of autonomy framework metrics for autonomous developers

George J. Hwang, Aniruddha Katre, Kyle M. Hart, Charles A. Rea

Proceedings Volume 12115, Autonomous Systems: Sensors, Processing and Security for Ground, Air, Sea and Space Vehicles and Infrastructure 2022; 121150F (2022) https://doi.org/10.1117/12.2623376
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

As autonomous systems proliferate, empirical measurement of their fitness is paramount. Several frameworks have been developed that provide guidance on what should be measured. However, these frameworks require users to develop their own metrics. Additionally, these frameworks focus on the autonomous systems rather than the enablers. An enabler could be the process used by developers. This research introduces novel techniques to analyze metrics used to measure fitness of autonomy architectures for developers. Crucially, this will be generalizable across autonomy measurement frameworks. The results are new techniques acquisition professionals can use to help better make tradeoffs development-wise for different architectures.

Conference Presentation

Citation Download Citation

George J. Hwang, Aniruddha Katre, Kyle M. Hart, and Charles A. Rea "Analysis techniques of autonomy framework metrics for autonomous developers", Proc. SPIE 12115, Autonomous Systems: Sensors, Processing and Security for Ground, Air, Sea and Space Vehicles and Infrastructure 2022, 121150F (6 June 2022); https://doi.org/10.1117/12.2623376

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