The OODA Loop of Cloudlet-Based Autonomous Drones

We present a benchmark-driven experimental study of autonomous drone agility relative to edge offload pipeline attributes. This pipeline includes a monocular gimbal-actuated on-drone camera, hardware RTSP video encoding, 4G LTE wireless network transmission, and computer vision processing on a ground-based GPU-equipped cloudlet. Our parameterized and reproducible agility benchmarks stress the OODA (“Observe, Orient, Decide, Act”) loop of the drone on obstacle avoidance and object tracking tasks. We characterize the latency and throughput of components of this OODA loop through software profiling, and identify opportunities for optimization.

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Publication Details

Published
2024-12-04
DOI
https://doi.org/10.1109/sec62691.2024.00022
Citations
1
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.35

Funders

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The OODA Loop of Cloudlet-Based Autonomous Drones

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article

The OODA Loop of Cloudlet-Based Autonomous Drones

Jingao Xu, Mahadev Satyanarayanan, Thomas Eiszler, Xiangliang Chen, Padmanabhan Pillai, Qifei Dong, Mihir Bala, Aditya Chanana
article en
1 citations

Abstract

We present a benchmark-driven experimental study of autonomous drone agility relative to edge offload pipeline attributes. This pipeline includes a monocular gimbal-actuated on-drone camera, hardware RTSP video encoding, 4G LTE wireless network transmission, and computer vision processing on a ground-based GPU-equipped cloudlet. Our parameterized and reproducible agility benchmarks stress the OODA (“Observe, Orient, Decide, Act”) loop of the drone on obstacle avoidance and object tracking tasks. We characterize the latency and throughput of components of this OODA loop through software profiling, and identify opportunities for optimization.

Intel (United States) (US), Carnegie Mellon University (US)
National Science Foundation
Openalex Percentile: Top 35%
IoT and Edge/Fog Computing
0.35
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