Assuring autonomy

Ramesh Bharadwaj

doi:10.1117/12.2557564

18 May 2020 Assuring autonomy

Ramesh Bharadwaj

Proceedings Volume 11419, Disruptive Technologies in Information Sciences IV; 114190G (2020) https://doi.org/10.1117/12.2557564
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

Autonomous systems, including self-driving cars and air vehicles, have caught the imagination of the press and the public. However, broader adoption of such systems in safety-critical applications has been the subject of intense debate and scrutiny. The stunning performance of deep learners compared to extant methods, including pattern matching, statistical methods, and legacy machine learning algorithms, has taken the research world by storm. This has naturally led the DoD community to ask the question: “How do we harness this technology being unleashed upon the world?” Before we answer this question, however, it is important to note that trust is integral to DoD applications, including autonomous systems, and ensuring reliable system operations is paramount. Therefore, we need strategies that harness deep learning algorithms to provide the DoD with autonomous systems that are robust, secure, timely and dependable.

Citation Download Citation

Ramesh Bharadwaj "Assuring autonomy", Proc. SPIE 11419, Disruptive Technologies in Information Sciences IV, 114190G (18 May 2020); https://doi.org/10.1117/12.2557564

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