Hybrid F' and ROS2 Architecture for Vision-Based Autonomous Flight: Design and Experimental Validation

2026-02-17

AI Summary

This work addresses the challenge of simultaneously achieving certifiable real-time control and advanced perception capabilities in autonomous flight systems, a balance that existing architectures struggle to maintain due to inherent trade-offs between reliability and flexibility. To bridge this gap, the authors propose a hybrid architecture that integrates NASA’s F´ flight software framework with the ROS 2 middleware, leveraging Protocol Buffers for efficient communication between vision-based navigation and flight control modules. Implemented and validated in closed-loop on an embedded quadrotor platform, this approach represents the first seamless integration of the certifiable F´ framework with the flexible ROS 2 ecosystem. Flight tests totaling 32.25 minutes demonstrate high performance: position estimation at 87.19 Hz, 99.90% data continuity, an average latency of 11.47 ms, only 15.19% CPU utilization, and successful execution of all 15 ground commands, collectively confirming the system’s efficiency, robustness, and certification potential.

Technology Category

• Intelligent Robots: State Estimation
• Application Domains: Mobility, Driving & Flight
• Natural Language Processing: Safety and Robustness

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Federated Web and WoT systems, including distributed, federated and edge-based data processing
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Browser and end-point security

Abstract

Autonomous aerospace systems require architectures that balance deterministic real-time control with advanced perception capabilities. This paper presents an integrated system combining NASA's F' flight software framework with ROS2 middleware via Protocol Buffers bridging. We evaluate the architecture through a 32.25-minute indoor quadrotor flight test using vision-based navigation. The vision system achieved 87.19 Hz position estimation with 99.90\% data continuity and 11.47 ms mean latency, validating real-time performance requirements. All 15 ground commands executed successfully with 100 % success rate, demonstrating robust F'--PX4 integration. System resource utilization remained low (15.19 % CPU, 1,244 MB RAM) with zero stale telemetry messages, confirming efficient operation on embedded platforms. Results validate the feasibility of hybrid flight-software architectures combining certification-grade determinism with flexible autonomy for autonomous aerial vehicles.

Problem

• autonomous flight
• real-time control
• perception
• flight software architecture
• determinism

Innovation

• F' framework
• ROS2 middleware
• Protocol Buffers bridging
• vision-based navigation
• real-time autonomous flight