Autonomous Learning Systems and Behaviors Focus Area

Abstract

Autonomous Learning Systems and Behaviors prototypes demonstrate capabilities to enhance the lethality of the joint force, reduce the time to make critical decisions, and protect warfighters through increased use of autonomous and human-machine collaborative systems. Selected projects leverage advances in machine learning to transfer cognitive burden closer to the point of collection and action. Example projects include agile computer vision systems; enhanced capabilities for multiple autonomous systems to cooperatively interact; autonomous task discrimination and prioritization; autonomous operation in complex terrain; optimization of autonomous supply delivery in contested environments; data preprocessing to improve ex-filtration from unmanned sensors; human-machine collaborative decision making; and, experiments to counter emerging unmanned threats from potential adversaries. These projects will also examine common software platforms and modular open architecture systems to reduce development cost, increase collaboration among manned and unmanned vehicles, increase agility through rapid customization, and inform requirements.

Document Details

Document Type
Accomplishment
Publication Date
Oct 01, 2021
Source ID
5c3f488ae4dfc8d528a871266d6ba1b6

Tags

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - Human-Robot Interaction
  • Autonomy - UAVs

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