Autonomous Teammates for Squad Tactics
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Authors
Tyler, James
Arnold, Ross
Abruzzo, Benjamin
Korpela, Christopher M.
Issue Date
2020-09
Type
proceedings-article
Language
Keywords
Force , Buildings , Object detection , Object recognition , Reconnaissance , Neural Networks , US Department of Defense
Alternative Title
Abstract
The United States Department of Defense seeks to integrate small unmanned aircraft systems (UAS) into infantry squads and develop tactics, techniques, and procedures using unmanned systems. Through an iterative design process consisting of live-fly tactical exercises, this research investigates the teaming of humans with unmanned aerial systems. Exercises involve force on force engagements to encourage the development of tactics and procedures for the future operating environment. Three successful mission tactics for leveraging UAS in missions are defined. In addition to autonomy, teams leverage convolutional and artificial deep neural networks running real time on aerial video feeds to identify and classify combatants and friendly forces.
Description
Citation
J. Tyler, R. Arnold, B. Abruzzo and C. Korpela, "Autonomous Teammates for Squad Tactics," 2020 International Conference on Unmanned Aircraft Systems (ICUAS), Athens, Greece, 2020, pp. 1667-1672, doi: 10.1109/ICUAS48674.2020.9213830.
Publisher
IEEE