将无人机碰撞测试数据转化为运行时安全限速，保障近人飞行安全。
From Bench to Flight: Translating Drone Impact Tests into Operational Safety Limits
- 搭建可复现的碰撞测试平台，获取不同机型与表面的力-时间数据。
- 建立速度与冲量、接触时长的映射模型，直接计算安全速度上限。
- 开源实时限速脚本与日志工具，支持特定场所安全策略部署。
室内微型飞行器（MAVs）日益用于需近距离接近人员的任务，但从业者缺乏基于实测撞击风险调整运动限制的实际方法。本文提出一个端到端、开源的工具链，将台架碰撞测试结果转化为可部署的无人机安全限速机制。首先，设计了一套紧凑且可复现的碰撞测试装置与流程，用于采集多类无人机与不同接触表面的力-时间曲线。其次，构建数据驱动模型，将撞击前速度映射为冲量与接触时长，实现针对目标受力阈值的速度上限直接计算。第三，发布可用于实时执行速度约束的ROS2节点及配套脚本，并支持设施定制化安全策略。我们在多款商用四旋翼无人机及典型室内设备上验证了该流程，结果表明所推导的安全限速机制在保持任务效率的同时，满足安全相关方规定的受力限制。本研究贡献在于建立从实测撞击到运行时安全边界的实用桥梁，提供可共享的数据集、代码与可复现流程，使团队能据此认证近人飞行操作的安全性。
原文摘要 · Abstract (English)
Indoor micro-aerial vehicles (MAVs) are increasingly used for tasks that require close proximity to people, yet practitioners lack practical methods to tune motion limits based on measured impact risk. We present an end-to-end, open toolchain that converts benchtop impact tests into deployable safety governors for drones. First, we describe a compact and replicable impact rig and protocol for capturing force-time profiles across drone classes and contact surfaces. Second, we provide data-driven models that map pre-impact speed to impulse and contact duration, enabling direct computation of speed bounds for a target force limit. Third, we release scripts and a ROS2 node that enforce these bounds online and log compliance, with support for facility-specific policies. We validate the workflow on multiple commercial off-the-shelf quadrotors and representative indoor assets, demonstrating that the derived governors preserve task throughput while meeting force constraints specified by safety stakeholders. Our contribution is a practical bridge from measured impacts to runtime limits, with shareable datasets, code, and a repeatable process that teams can adopt to certify indoor MAV operations near humans.
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