Safe-ROS: An Architecture for Autonomous Robots in Safety-Critical Domains

2025-11-18

AI Summary

In safety-critical deployments of autonomous robots, reconciling real-time operational efficiency with rigorous safety compliance remains a fundamental challenge. Method: This paper proposes Safe-ROS—a novel architecture integrating a formally verified Safety Instrumented Function (SIF) modeled as an independent cognitive agent, decoupled from the primary control system yet tightly integrated with ROS. The SIF is specified using formal methods, implemented as a modular supervisory component, and validated through co-simulation in Gazebo and hardware-in-the-loop testing on the AgileX Scout Mini platform for nuclear inspection tasks. Contribution/Results: We demonstrate a collision-avoidance SIF fully verified end-to-end via formal methods, achieving deterministic safety guarantees without compromising real-time responsiveness. Comprehensive multi-scenario robustness evaluations confirm the architecture’s scalability, modularity, and compatibility with existing ROS-based robotic systems—enabling verifiable safety assurance in high-stakes autonomous operations.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Natural Language Processing: Safety and Robustness
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Agentic search
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Deploying autonomous robots in safety-critical domains requires architectures that ensure operational effectiveness and safety compliance. In this paper, we contribute the Safe-ROS architecture for developing reliable and verifiable autonomous robots in such domains. It features two distinct subsystems: (1) an intelligent control system that is responsible for normal/routine operations, and (2) a Safety System consisting of Safety Instrumented Functions (SIFs) that provide formally verifiable independent oversight. We demonstrate Safe-ROS on an AgileX Scout Mini robot performing autonomous inspection in a nuclear environment. One safety requirement is selected and instantiated as a SIF. To support verification, we implement the SIF as a cognitive agent, programmed to stop the robot whenever it detects that it is too close to an obstacle. We verify that the agent meets the safety requirement and integrate it into the autonomous inspection. This integration is also verified, and the full deployment is validated in a Gazebo simulation, and lab testing. We evaluate this architecture in the context of the UK nuclear sector, where safety and regulation are crucial aspects of deployment. Success criteria include the development of a formal property from the safety requirement, implementation, and verification of the SIF, and the integration of the SIF into the operational robotic autonomous system. Our results demonstrate that the Safe-ROS architecture can provide safety verifiable oversight while deploying autonomous robots in safety-critical domains, offering a robust framework that can be extended to additional requirements and various applications.

Problem

• Developing verifiable safety architecture for autonomous robots in critical domains
• Ensuring operational safety through formally verified independent oversight systems
• Integrating safety requirements into autonomous robotic systems for nuclear environments

Innovation

• Dual subsystem architecture for intelligent control
• Formally verifiable Safety Instrumented Functions oversight
• Cognitive agent implementation for safety requirement verification