Integrating Machine Learning Compute Mechanisms for Unmanned Aerial Vehicle Control

We present a novel integration of Pixhawk autopilot technology with a Jetson Nano for real-time mission control using Computer Vision (CV). The Pixhawk (PX4) autopilot system provides a robust platform for autonomous missions in unmanned aerial vehicles (UAVs), offering precise control and navigation capabilities. The system gains precise and efficient onboard processing capabilities by incorporating the Jetson Nano, a powerful AI computing device, alongside the PX4. Leveraging CV algorithms, the integrated system can autonomously analyze visual data from multiple cameras in real time, allowing for dynamic changes during flight missions. This enables the UAV to respond quickly to obstacles and changing environmental conditions, changing the mission as necessary. We aim to highlight the synergy between the Jetson and the PX4, demonstrating their combined potential to enhance UAV autonomy through intelligent CV-based mechanisms.

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Publication Details

Journal
UA Campus Repository (The University of Arizona)
Published
2024-10-01
Primary Topic
UAV Applications and Optimization
Type
article
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article

Integrating Machine Learning Compute Mechanisms for Unmanned Aerial Vehicle Control

UA Campus Repository (The University of Arizona)
UAV Applications and Optimization
article

Integrating Machine Learning Compute Mechanisms for Unmanned Aerial Vehicle Control

article en

Abstract

We present a novel integration of Pixhawk autopilot technology with a Jetson Nano for real-time mission control using Computer Vision (CV). The Pixhawk (PX4) autopilot system provides a robust platform for autonomous missions in unmanned aerial vehicles (UAVs), offering precise control and navigation capabilities. The system gains precise and efficient onboard processing capabilities by incorporating the Jetson Nano, a powerful AI computing device, alongside the PX4. Leveraging CV algorithms, the integrated system can autonomously analyze visual data from multiple cameras in real time, allowing for dynamic changes during flight missions. This enables the UAV to respond quickly to obstacles and changing environmental conditions, changing the mission as necessary. We aim to highlight the synergy between the Jetson and the PX4, demonstrating their combined potential to enhance UAV autonomy through intelligent CV-based mechanisms.

UA Campus Repository (The University of Arizona)
University of Arizona (US)
Openalex Percentile: Top 23%
UAV Applications and Optimization
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