ROAIJun 5

An Abstract Architecture for Explainable Autonomy in Hazardous Environments

arXiv:2606.072114.92 citations
Predicted impact top 77% in RO · last 90 daysOriginality Synthesis-oriented
AI Analysis

For engineers and designers of autonomous systems in hazardous environments, this architecture provides a template to incorporate explainability from the start, addressing the need for trust among users and regulators.

The paper proposes an abstract architecture for designing explainable autonomous systems, aimed at enhancing user trust in hazardous environments. A worked example in the civil nuclear industry demonstrates its applicability.

Autonomous robotic systems are being proposed for use in hazardous environments, often to reduce the risks to human workers. In the immediate future, it is likely that human workers will continue to use and direct these autonomous robots, much like other computerised tools but with more sophisticated decision-making. Therefore, one important area on which to focus engineering effort is ensuring that these users trust the system. Recent literature suggests that explainability is closely related to how trustworthy a system is. Like safety and security properties, explainability should be designed into a system, instead of being added afterwards. This paper presents an abstract architecture that supports an autonomous system explaining its behaviour (explainable autonomy), providing a design template for implementing explainable autonomous systems. We present a worked example of how our architecture could be applied in the civil nuclear industry, where both workers and regulators need to trust the system's decision-making capabilities.

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