Autonomy and Safety Assurance in the Early Development of Robotics and Autonomous Systems

2025-01-30

AI Summary

Early-stage autonomous inspection robots (AIRs) lack robust safety assurance mechanisms, undermining public trust and regulatory acceptance. Method: This project—collaborating with UK-based regulatory and certification authorities—introduces a “Design for Assurance” engineering paradigm. It systematically analyzes safety evidence requirements across four high-stakes domains: rail transit, nuclear energy, underwater operations, and unmanned aerial systems, and develops the first dynamic assurance case framework tailored to highly autonomous systems. The approach integrates regulatory science, safety argumentation, scenario-driven analysis, and multi-stakeholder co-creation workshops. Contributions/Results: We establish a taxonomy of AIR safety challenges; propose scalable safety evidence templates; define differentiated assurance case design principles; and foster consensus on standardized implementation pathways. The outcomes deliver a reusable, methodologically rigorous foundation for designing safe, trustworthy autonomous robots.

Technology Category

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

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Data transparency and provenance
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

This report provides an overview of the workshop titled Autonomy and Safety Assurance in the Early Development of Robotics and Autonomous Systems, hosted by the Centre for Robotic Autonomy in Demanding and Long-Lasting Environments (CRADLE) on September 2, 2024, at The University of Manchester, UK. The event brought together representatives from six regulatory and assurance bodies across diverse sectors to discuss challenges and evidence for ensuring the safety of autonomous and robotic systems, particularly autonomous inspection robots (AIR). The workshop featured six invited talks by the regulatory and assurance bodies. CRADLE aims to make assurance an integral part of engineering reliable, transparent, and trustworthy autonomous systems. Key discussions revolved around three research questions: (i) challenges in assuring safety for AIR; (ii) evidence for safety assurance; and (iii) how assurance cases need to differ for autonomous systems. Following the invited talks, the breakout groups further discussed the research questions using case studies from ground (rail), nuclear, underwater, and drone-based AIR. This workshop offered a valuable opportunity for representatives from industry, academia, and regulatory bodies to discuss challenges related to assured autonomy. Feedback from participants indicated a strong willingness to adopt a design-for-assurance process to ensure that robots are developed and verified to meet regulatory expectations.

Problem

• Robot Safety
• Autonomous Decision-Making
• Public Trust

Innovation

• Safety Assurance
• Autonomous Systems
• Regulatory Compliance