Hazard Management in Robot-Assisted Mammography Support
- URL: http://arxiv.org/abs/2604.05749v1
- Date: Tue, 07 Apr 2026 11:52:02 GMT
- Title: Hazard Management in Robot-Assisted Mammography Support
- Abstract summary: MammoBot is an assistive robotic system designed to support patients during X-ray mammography.<n>This paper presents a hazard management methodology for MammoBot.
- Score: 4.4103353984747935
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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.
Related papers
- Clinical Pathways as Safety Specifications for Physical AI in Hospital Wards [2.479074862022315]
This paper reinterprets Clinical Pathways as explicit runtime safety specifications for embodied medical AI.<n>We propose a conceptual robotic architecture that integrates wearable sensors, smart medical devices, and assistive robotic components into a unified framework for real-time safety monitoring.
arXiv Detail & Related papers (2026-07-22T07:02:11Z) - Safety in Embodied AI: A Survey of Risks, Attacks, and Defenses [168.50301366360344]
Embodied Artificial Intelligence (Embodied AI) integrates perception, cognition, planning, and interaction into agents that operate in safety-critical environments.<n>Unlike digital AI systems, embodied agents must act under uncertain sensing, incomplete knowledge, and dynamic human-robot interactions.<n>This survey provides a comprehensive review of safety research in embodied AI, examining attacks and defenses across the full embodied pipeline.
arXiv Detail & Related papers (2026-03-28T13:21:44Z) - ANNIE: Be Careful of Your Robots [48.89876809734855]
We present the first systematic study of adversarial safety attacks on embodied AI systems.<n>We show attack success rates exceeding 50% across all safety categories.<n>Results expose a previously underexplored but highly consequential attack surface in embodied AI systems.
arXiv Detail & Related papers (2025-09-03T15:00:28Z) - Uncertainty Aware-Predictive Control Barrier Functions: Safer Human Robot Interaction through Probabilistic Motion Forecasting [13.020006323600251]
Uncertainty-Aware Predictive Control Barrier Functions fuses probabilistic human hand motion forecasting with the formal safety guarantees of Control Barrier Functions.<n> UA-PCBFs empower collaborative robots with a deeper understanding of future human states.<n>Relative to state-of-the-art HRI architectures, UA-PCBFs show better performance in task-critical metrics.
arXiv Detail & Related papers (2025-08-28T14:11:26Z) - A Verification Methodology for Safety Assurance of Robotic Autonomous Systems [0.1962656580942496]
This paper presents a verification workflow for the safety assurance of an autonomous agricultural robot.<n>It covers the entire development life-cycle, from concept study and design to runtime verification.<n>Results show that the methodology can be effectively used to verify safety-critical properties and facilitate the early identification of design issues.
arXiv Detail & Related papers (2025-06-24T13:39:51Z) - Probabilistic modelling and safety assurance of an agriculture robot providing light-treatment [0.0]
Continued adoption of agricultural robots postulates the farmer's trust in the reliability, robustness and safety of the new technology.<n>This paper considers a probabilistic modelling and risk analysis framework for use in the early development phases.
arXiv Detail & Related papers (2025-06-24T13:39:32Z) - An Approach to Technical AGI Safety and Security [72.83728459135101]
We develop an approach to address the risk of harms consequential enough to significantly harm humanity.<n>We focus on technical approaches to misuse and misalignment.<n>We briefly outline how these ingredients could be combined to produce safety cases for AGI systems.
arXiv Detail & Related papers (2025-04-02T15:59:31Z) - HAICOSYSTEM: An Ecosystem for Sandboxing Safety Risks in Human-AI Interactions [95.49509269498367]
We present HAICOSYSTEM, a framework examining AI agent safety within diverse and complex social interactions.<n>We run 1840 simulations based on 92 scenarios across seven domains (e.g., healthcare, finance, education)<n>Our experiments show that state-of-the-art LLMs, both proprietary and open-sourced, exhibit safety risks in over 50% cases.
arXiv Detail & Related papers (2024-09-24T19:47:21Z) - EARBench: Towards Evaluating Physical Risk Awareness for Task Planning of Foundation Model-based Embodied AI Agents [53.717918131568936]
Embodied artificial intelligence (EAI) integrates advanced AI models into physical entities for real-world interaction.<n>Foundation models as the "brain" of EAI agents for high-level task planning have shown promising results.<n>However, the deployment of these agents in physical environments presents significant safety challenges.<n>This study introduces EARBench, a novel framework for automated physical risk assessment in EAI scenarios.
arXiv Detail & Related papers (2024-08-08T13:19:37Z) - Safety Control of Service Robots with LLMs and Embodied Knowledge Graphs [12.787160626087744]
We propose a novel integration of Large Language Models with Embodied Robotic Control Prompts (ERCPs) and Embodied Knowledge Graphs (EKGs)
ERCPs are designed as predefined instructions that ensure LLMs generate safe and precise responses.
EKGs provide a comprehensive knowledge base ensuring that the actions of the robot are continuously aligned with safety protocols.
arXiv Detail & Related papers (2024-05-28T05:50:25Z) - Leveraging Traceability to Integrate Safety Analysis Artifacts into the
Software Development Process [51.42800587382228]
Safety assurance cases (SACs) can be challenging to maintain during system evolution.
We propose a solution that leverages software traceability to connect relevant system artifacts to safety analysis models.
We elicit design rationales for system changes to help safety stakeholders analyze the impact of system changes on safety.
arXiv Detail & Related papers (2023-07-14T16:03:27Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.