Hybrid F' and ROS2 Architecture for Vision-Based Autonomous Flight: Design and Experimental Validation
About
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.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Position Estimation | Autonomous Inspection Mission (test) | Mean Error (m)-0.2645 | 3 | |
| Orientation Estimation | Autonomous inspection flight mission | Roll Mean Error (deg)-0.35 | 1 | |
| Vision system latency estimation | Autonomous inspection mission flight data (test) | Latency Mean (ms)11.47 | 1 |