用廉价无人机实现高精度集群飞行，降低科研门槛
AirSwarm: Enabling Cost-Effective Multi-UAV Research with COTS drones
- 分层控制+视觉定位，无需外部设备
- 厘米级定位精度，支持编队与轨迹跟踪
- 开源框架适配教学与研究场景
传统多无人机集群任务依赖昂贵定制无人机或外部定位系统，限制了科研与教育中的应用。为此，我们提出 AirSwarm，利用 Tello、Anafi 等低成本商用无人机实现可负担的多机协同研究与教学。核心创新包括：面向可靠多机协调的分层控制架构、无需外部动捕的基础设施免视效 SLAM 定位系统，以及基于 ROS 的简化集群开发软件框架。实验表明，系统可实现厘米级跟踪精度、低延迟控制、抗通信中断能力，并支持编队飞行与轨迹跟踪。通过降低资金与技术门槛，AirSwarm 使多机器人研究与教育更易普及。完整教程与开源代码将公开。
原文摘要 · Abstract (English)
Traditional unmanned aerial vehicle (UAV) swarm missions rely heavily on expensive custom-made drones with onboard perception or external positioning systems, limiting their widespread adoption in research and education. To address this issue, we propose AirSwarm. AirSwarm democratizes multi-drone coordination using low-cost commercially available drones such as Tello or Anafi, enabling affordable swarm aerial robotics research and education. Key innovations include a hierarchical control architecture for reliable multi-UAV coordination, an infrastructure-free visual SLAM system for precise localization without external motion capture, and a ROS-based software framework for simplified swarm development. Experiments demonstrate cm-level tracking accuracy, low-latency control, communication failure resistance, formation flight, and trajectory tracking. By reducing financial and technical barriers, AirSwarm makes multi-robot education and research more accessible. The complete instructions and open source code will be available at
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