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

2026-02-17 · Abdelrahman Metwally, Monijesu James, Aleksey Fedoseev, Miguel Altamirano Cabrera, Dzmitry Tsetserukou, Andrey Somov arxiv

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.

📄 PDF Abstract BibTeX arXiv:2602.15398

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Full Model-Free Control Architecture for Hybrid UAVs

2019-10-10 · journal 2019 10 · Jacson M. O. Barth1, Jean-Philippe Condomines1

This paper discusses the development of a control architecture for hybrid Unmanned Aerial Vehicles (UAVs) based on model-free control (MFC) algorithms. Hybrid UAVs combine the beneficial features of fixed-wing UAVs wi…

model Position

High-Speed Vision-Based Flight in Clutter with Safety-Shielded Reinforcement Learning

2026-02-09 · Jiarui Zhang, Chengyong Lei, Chengjiang Dai, Kenghou Hoi 외 arxiv

Quadrotor unmanned aerial vehicles (UAVs) are increasingly deployed in complex missions that demand reliable autonomous navigation and robust obstacle avoidance. However, traditional modular pipelines often incur cumulat…

Reinforcement Learning

Autonomous Navigation at the Nano-Scale: Algorithms, Architectures, and Constraints

2026-01-19 · Mahmud S. Zango, Jianglin Lan arxiv

Autonomous navigation for nano-scale unmanned aerial vehicles (nano-UAVs) is governed by extreme Size, Weight, and Power (SWaP) constraints (with the weight < 50 g and sub-100 mW onboard processor), distinguishing it fun…

Reinforcement Learning Visual Navigation Pose Estimation

Hardware- and Vision-in-the-Loop Validation of Deep Monocular Pose Estimation for Autonomous Maritime UAV Flight

2026-06-17 · Maneesha Wickramasuriya, Beomyeol Yu, Jaden Shin, Mason Huslig 외 arxiv

Autonomous UAV operations on ships require reliable vision-based relative pose estimation, yet at-sea validation is costly, weather-dependent, and risky. This paper presents a hardware-validated vision-in-the-loop framew…

Pose Estimation

MMH-Planner: Multi-Mode Hybrid Trajectory Planning Method for UAV Efficient Flight Based on Real-Time Spatial Awareness

2026-03-03 · Yinghao Zhao, Chenguang Dai, Liang Lyu, Zhenchao Zhang 외 arxiv

Motion planning is a critical component of intelligent unmanned systems, enabling their complex autonomous operations. However, current planning algorithms still face limitations in planning efficiency due to inflexible …

Trajectory Planning Motion Planning