Real-Time Artificial Intelligence/Machine Learning (AI/ML) on Platforms; Embedded High Performance Computing at the Edge

Abstract

This project developed and demonstrated an advanced, size, weight and power constrained, embedded AI/ML computing capability for integration and demonstration on an operationally relevant platform. The prototype consists of an optimized Agile Condor pod that delivers AI/ML capabilities at the sensor thereby providing real-time information to users on the ground. Using FY 2019 funding, the project completed system development, integration, and testing of the system on an MQ-9 unmanned aerial vehicle platform with on-board sensors. This integration effort provided the system with the flight certification required for future transition efforts onto operational MQ-9 platforms. The Agile Condor systems transitioned to the U.S. Air Force.

Document Details

Document Type
Accomplishment
Publication Date
Oct 01, 2021
Source ID
660d13e2c81495769a8f51e9f523479a

Tags

Fields of Study

  • Computer science
  • Engineering

Readers

  • Enterprise Information Systems Architecture and Joint Command Capability Interoperability Support.
  • Parallel and Distributed Computing.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy

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