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Proceedings Paper

Probabilistic reasoning for real-time UAV decision and control
Author(s): Brian Berthold; Trevor J. Bihl; Chadwick Cox; Todd A. Jenkins; Logan Leland
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Paper 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..

Paper Details

Date Published: 28 May 2019
PDF: 7 pages
Proc. SPIE 11017, Sensors and Systems for Space Applications XII, 110170A (28 May 2019); doi: 10.1117/12.2519451
Show Author Affiliations
Brian Berthold, Ohio Univ. (United States)
Trevor J. Bihl, Air Force Research Lab. (United States)
Chadwick Cox, KeyW Corp. (United States)
Todd A. Jenkins, Air Force Research Lab. (United States)
Logan Leland, KeyW Corp. (United States)

Published in SPIE Proceedings Vol. 11017:
Sensors and Systems for Space Applications XII
Genshe Chen; Khanh D. Pham, Editor(s)

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