arXiv:2607.19213cs.ROcs.AI2026-07

描绘未来十年无人机大规模运行的蓝图与关键技术挑战

Computing on the Fly: Navigating a Vision for the Future of Drone Computing

  • 提出12项核心挑战以实现无人机规模化安全运营
  • 涵盖从智能控制到基础设施保护的全链条技术需求
  • 适合政策制定者、科研人员和产业界参考

报告展望了未来十年,无人机将像高速公路和电网一样,大规模运输货物、医疗物资和信息。应用场景包括灾情中快速发现火源、绕过地面拥堵向偏远医院配送药品,以及全国性机群持续巡检桥梁和输电线路。但要实现这一愿景,必须弥补硬件与软件能力之间的“能力差距”。报告识别出十二项关键技术挑战:支持数百万架无人机的规模扩展;人工智能的智能与可信保障;边缘-云连续体与实时协同;人工智能自主与代理系统;数据、训练与验证基础设施;关键基础设施防护;从非确定性智能体构建可靠机群;信任、安全与分布式认证;下一代无人机网络;人机协作与可扩展洞察;标准、认证与监管;以及人才发展与教育。这些挑战及应对策略共同构成了推动无人机技术演进的多维度路径。

原文摘要 · Abstract (English)

The report envisions a decade in which drones move goods, medical supplies, and information at a scale comparable to national infrastructure investments like highways and the electric grid. Potential applications include natural disaster detection drones that spot wildfire sources within minutes, medical supply chains that bypass ground congestion to reach rural hospitals, and nationwide fleets that continuously inspect bridges and power lines. Realizing this future, however, requires closing what report authors call a "capability gap," where hardware and aspirations are outpacing the software and systems needed to operate safely at scale. The report identifies twelve technical challenges that must be addressed to realize the transformative potential of drone technology: Scaling to millions of drones; AI intelligence and assurance; Edge-cloud continuum and real-time coordination; AI autonomy and agentic systems; Data, training, and validation infrastructure; Critical infrastructure protection; Building reliable fleets from non-deterministic agents; Trust, security, and distributed authentication; Next-generation drone networks; Human-AI partnership and scalable insight; Standards, certification, and regulation; and Workforce development and education. These twelve challenges and proposed approaches to them form the basis of the report, laying out a multifaceted path forward for the evolution of done technology.

无人机智能系统未来科技基础设施

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