Probabilistic reasoning for real-time UAV decision and control

Brian Berthold; Trevor J. Bihl; Chadwick Cox; Todd A. Jenkins; Logan Leland

doi:10.1117/12.2519451

28 May 2019 Probabilistic reasoning for real-time UAV decision and control

Brian Berthold, Trevor J. Bihl, Chadwick Cox, Todd A. Jenkins, Logan Leland

Proceedings Volume 11017, Sensors and Systems for Space Applications XII; 110170A (2019) https://doi.org/10.1117/12.2519451
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

Developing onboard abilities to control and task unmanned vehicles (UxVs) and swarms of UxVs is key to both wider use of systems. Herein, the authors develop and apply a probabilistic reasoning framework for UxVs. The reasoning system considers tasks, in this case search and rescue, based on both prior knowledge and sensor feedback. The approach considered is an imperative program to generate situation de-scriptions and decision problems as probabilistic, declarative programs. This operation replaces human tasking of UxVs. Results indicate a significant decrease in swarm fuel usage when compared to manned tasking of assets for the same task..

Citation Download Citation

Brian Berthold, Trevor J. Bihl, Chadwick Cox, Todd A. Jenkins, and Logan Leland "Probabilistic reasoning for real-time UAV decision and control", Proc. SPIE 11017, Sensors and Systems for Space Applications XII, 110170A (28 May 2019); https://doi.org/10.1117/12.2519451

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