arXiv:2604.05749cs.ROcs.SY2026-04

为乳腺摄影机器人设计安全防护机制,防误操作与状态误解

Hazard Management in Robot-Assisted Mammography Support

  • 用多方协作定义人机交互流程,结合SHARD与STPA识别风险
  • 发现多数隐患源于时间错配和状态误判,非设备故障
  • 生成可追踪的安全需求,减少对人工判断的依赖

机器人与具身人工智能系统有望提升临床诊疗的可及性与质量,但其在与脆弱患者近距离接触时带来显著安全风险。本文提出针对MammoBot——一种用于辅助乳腺X光检查的机器人系统——的危害管理方法。为确保从早期开发阶段即保障安全,采用利益相关者指导的过程建模,结合软件危害分析与设计中化解(SHARD)和系统理论过程分析(STPA)。人机交互流程由临床医生、机器人专家及患者代表共同定义,以捕捉关键互动环节。利用SHARD识别技术与程序偏差,通过STPA分析用户交互引发的不安全控制行为。结果表明,许多危害并非源于部件失效,而是由于时间错配、过早操作及系统状态误读。这些隐患被转化为更精确的安全要求,约束系统行为,降低对人工正确时机或理解的依赖。该工作展示了一种结构化且可追溯的安全驱动设计方法,具有向其他临床辅助机器人系统推广的潜力。

原文摘要 · Abstract (English)

Robotic and embodied-AI systems have the potential to improve accessibility and quality of care in clinical settings, but their deployment in close physical contact with vulnerable patients introduces significant safety risks. This paper presents a hazard management methodology for MammoBot, an assistive robotic system designed to support patients during X-ray mammography. To ensure safety from early development stages, we combine stakeholder-guided process modelling with Software Hazard Analysis and Resolution in Design (SHARD) and System-Theoretic Process Analysis (STPA). The robot-assisted workflow is defined collaboratively with clinicians, roboticists, and patient representatives to capture key human-robot interactions. SHARD is applied to identify technical and procedural deviations, while STPA is used to analyse unsafe control actions arising from user interaction. The results show that many hazards arise not from component failures, but from timing mismatches, premature actions, and misinterpretation of system state. These hazards are translated into refined and additional safety requirements that constrain system behaviour and reduce reliance on correct human timing or interpretation alone. The work demonstrates a structured and traceable approach to safety-driven design with potential applicability to assistive robotic systems in clinical environments.

机器人医疗安全设计人机交互

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