Enabling Seamless HRC Integration: The AIPRISM Reference Architecture

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Authors: Miguel A. Mateo-Casalí, Josep Rueda, Samuel Olaiya Afolaranmi, Jose Luis Martinez Lastra, Davide Boscaini, Laura Moya-Ruiz, and Francisco Fraile
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Abstract

This article addresses the challenges of deploying AI solutions for human-robot collaboration (HRC) in the context of industry 5.0, introducing the AI-PRISM framework as a solving proposal. This framework presents a high-level reference architecture which is designed to provide efficient and adaptive robotic systems in industrial environments, using Kubernetes clusters managed through Rancher to ensure reliability and easy maintenance and monitorization. The four tiers identified in this architecture start from the lower levels with the physical devices in the Device Tier, followed by the Ambient Network Tier to ensure that real-time communication required in any human-robot collaboration environment. The Fog Tier involves more processing capacity and resources, but keeping almost real-time responses, therefore, modules related with reasoning, perception and simulation are here. The Enterprise Tier focuses on Continuous Integration and Deployment (CI/CD), allowing to deploy components, and nonreal-time modules. In addition to the Reference Architecture components, the AI-PRISM Open-Access Platform is a web-based gateway, that provides stakeholders access to tools, technologies, and resources, encouraging collaboration, experimentation and testing in AI-based collaborative robotics.

Fields of Study & Subjects

Robotics and Automated Systems Robot Manipulation and Learning Digital Transformation in Industry

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
27 February 2026
Language
EN