An Industry 5.0 Compliant Human-Robot Collaboration Digital Twin Framework for African Medium Scale Enterprises - Fasina, Ebun-Oluwa Phillip; Sawyerr, Babatunde Alade; Akinola-Taiwo, Kayodele; Murainah, Abdul-Azeez; Ojiako, Chika Perpetua (AI Society & STMIK Indonesia, 2025)
Industry 5.0 emphasizes human-robot collaboration, where Digital Twins (DTs) connect physical and digital operations for efficient, flexible work. Existing DT frameworks often focus on full-system autonomy or prediction, overlooking structured, task-level coordination between Human and Robot Digital Twins (HDT and RDT). This paper introduces a minimal, modular framework that enables shared task-based collaboration between HDT and RDT agents. Built on the Cross Domain Digital Twin (CDDT) design pattern, it supports real-time, role-specific interaction. The framework provides a scalable foundation for collaborative DT systems aligned with Industry 5.0, offering a practical base for future human–robot coordination research.