融合F'与ROS2实现视觉导航无人机的实时稳定飞行
Hybrid F' and ROS2 Architecture for Vision-Based Autonomous Flight: Design and Experimental Validation
- 用Protocol Buffers连接NASA F'与ROS2，兼顾确定性与灵活性
- 32分钟飞行中位置估计达87.19Hz，延迟仅11.47ms，数据连续性99.90%
- 适合需高可靠性与智能感知结合的航空系统开发者
自主航空航天系统需要在确定性实时控制与先进感知能力之间取得平衡。本文提出一种集成架构，通过Protocol Buffers桥接NASA的F'飞行软件框架与ROS2中间件。我们通过一次32.25分钟的室内四轴飞行测试验证该架构，视觉系统实现87.19 Hz的位置估计，数据连续性达99.90%，平均延迟为11.47 ms，满足实时性要求。所有15条地面指令均成功执行（成功率100%），证明了F'与PX4的稳健集成。系统资源占用低（CPU 15.19%，RAM 1,244 MB），无滞留遥测消息，表明其可在嵌入式平台高效运行。结果验证了混合飞行软件架构的可行性，可将认证级确定性与灵活自主能力结合用于自主飞行器。
原文摘要 · Abstract (English)
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.
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