From Bench to Flight: Translating Drone Impact Tests into Operational Safety Limits

TL;DR

This paper introduces an open, practical toolchain that translates impact test data into real-time safety limits for indoor drones, ensuring safety compliance without sacrificing operational efficiency.

Contribution

It provides a complete, shareable workflow and tools for converting impact measurements into enforceable safety bounds for drone operation near humans.

Findings

Validated on commercial drones and indoor assets

Maintains task throughput while meeting safety force limits

Provides open datasets, code, and a repeatable process

Abstract

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.