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Abstract <p>Unmanned aerial vehicles, particularly autonomous and self-organizing copter swarms, are a cornerstone of contemporary technology ecosystems, revolutionizing industries such as surveillance, environmental monitoring, logistics, and disaster management. However, their reliance on satellite-based navigation systems, such as Global Positioning System, leaves them highly vulnerable to hostile strategies like signal jamming, spoofing, and denial-of-service attacks, critically undermining their functionality in global navigation satellite systems denied environments. This research introduces a satellite-independent method for copter hovering and stabilization that directly enhances the autonomy and adaptability of self-organizing unmanned aerial vehicle swarms. Leveraging optical flow, a vision-based technique for detecting motion patterns, in combination with onboard sensors such as inertial measurement units, the proposed system enables reliable, real-time hovering and stabilization. This approach not only ensures robust individual drone performance in global navigation satellite systems degraded or denied environments-including dense urban areas, subterranean spaces, and subterranean spaces but also strengthens the swarm’s ability to self-organize, maintain formation, and adapt dynamically to environmental disruptions. In the context of copter unmanned aerial vehicles and self-organizing swarms, stable hovering and in-air stabilization are essential to prevent platform losses and ensure continuous system coordination. Maintaining a fixed position enables each unmanned aerial vehicle to reliably exchange sensor and mission-critical data with neighboring swarm members and/or with a centralized data storage node in a cloud. This functionality is crucial for mission adaptability, allowing the human operator or autonomous mission planner to dynamically reorganize tasks based on the real-time status and availability of individual unmanned aerial vehicles. In the absence of global navigation satellite systems, achieving such stabilization through onboard sensing and control is vital for the resilience and effectiveness of decentralized swarm operations, particularly in contested, cluttered, or communication-constrained environments.</p>

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Vision-Based Hover Stabilization of Copter Unmanned Aerial Vehicles Using Raspberry Pi in the Absence of Global Navigation Satellite Systems

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • Agit Atashyan,
  • Norayr Aslanyan,
  • Vahagn Poghosyan,
  • Suren Poghosyan

摘要

Abstract

Unmanned aerial vehicles, particularly autonomous and self-organizing copter swarms, are a cornerstone of contemporary technology ecosystems, revolutionizing industries such as surveillance, environmental monitoring, logistics, and disaster management. However, their reliance on satellite-based navigation systems, such as Global Positioning System, leaves them highly vulnerable to hostile strategies like signal jamming, spoofing, and denial-of-service attacks, critically undermining their functionality in global navigation satellite systems denied environments. This research introduces a satellite-independent method for copter hovering and stabilization that directly enhances the autonomy and adaptability of self-organizing unmanned aerial vehicle swarms. Leveraging optical flow, a vision-based technique for detecting motion patterns, in combination with onboard sensors such as inertial measurement units, the proposed system enables reliable, real-time hovering and stabilization. This approach not only ensures robust individual drone performance in global navigation satellite systems degraded or denied environments-including dense urban areas, subterranean spaces, and subterranean spaces but also strengthens the swarm’s ability to self-organize, maintain formation, and adapt dynamically to environmental disruptions. In the context of copter unmanned aerial vehicles and self-organizing swarms, stable hovering and in-air stabilization are essential to prevent platform losses and ensure continuous system coordination. Maintaining a fixed position enables each unmanned aerial vehicle to reliably exchange sensor and mission-critical data with neighboring swarm members and/or with a centralized data storage node in a cloud. This functionality is crucial for mission adaptability, allowing the human operator or autonomous mission planner to dynamically reorganize tasks based on the real-time status and availability of individual unmanned aerial vehicles. In the absence of global navigation satellite systems, achieving such stabilization through onboard sensing and control is vital for the resilience and effectiveness of decentralized swarm operations, particularly in contested, cluttered, or communication-constrained environments.