Test and evaluation needs of multi-domain autonomous systems

Erik Blasch; Yu Chen; Dan Shen; Genshe Chen

doi:10.1117/12.2559031

18 May 2020 Test and evaluation needs of multi-domain autonomous systems

Erik Blasch, Yu Chen, Dan Shen, Genshe Chen

Proceedings Volume 11413, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications II; 1141308 (2020) https://doi.org/10.1117/12.2559031
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

The paper highlights the need for methods of analytical science for multi-domain autonomy evaluation. Multidomain autonomous systems need to collect large amounts of data to verify, validate, test, and evaluate system operations. For multi-domain and uncertain scenarios, data sampling may not be adequate to fully explore and represent the entire trade space for verification and validation (V&V). However, leveraging methods from test and evaluation (T&E), a hierarchy of analytics can be developed so as to narrow the trade space. Issues in V&V/T&E employ statistics, but could benefit from first-principles physics theoretical analytics, data augmentation, and scenario design. The use of modeling is not new; however, as analytics of artificial intelligence and machine learning (AI/ML) are designed to exploit data; then there are opportunities to allow one domain (e.g., air) support data analytics in another domain (e.g., cyber).

Conference Presentation

Citation Download Citation

Erik Blasch, Yu Chen, Dan Shen, and Genshe Chen "Test and evaluation needs of multi-domain autonomous systems", Proc. SPIE 11413, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications II, 1141308 (18 May 2020); https://doi.org/10.1117/12.2559031

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