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This paper presents an integrated framework that combines advanced visual perception, continuous ergonomic monitoring, and adaptive Behaviour Tree (BT) decision-making. We adopt a supervisory human-robot collaboration paradigm in which the robot provides temporary, ergonomics-driven assistance only when real-time OWAS assessment indicates hazardous conditions (classes 3-4) and returns execution to the operator as risk subsides, preserving human primacy (97.4% human-led operations in our study). Our modular, scalable approach synthesizes deep learning models, advanced tracking, and dynamic ergonomic assessment. Experimental validation in controlled laboratory settings with industrial-grade sensing and simulation-in-the-loop actuation demonstrates strong performance across multiple dimensions: the perception module achieves 72.4% mAP@50:95; grasp-intention recognition reaches 92.5%; ergonomic risks are classified with 0.081\u00a0s mean pose-monitoring latency (95% CI [0.072, 0.093]); and BT policies trigger robotic interventions with 0.07\u00a0s decision-layer latency (tick-to-trigger)\u2014approximately 56% faster than a representative prior HRC controller under comparable tasks\u2014while the integrated end-to-end response averages 0.452\u00a0s (95% CI [0.283, 0.622]) while maintaining auditable, deterministic safety logic. This comprehensive solution provides a robust platform for enhancing human-robot collaboration in industrial environments by prioritizing ergonomic safety, operational efficiency, and real-time adaptability.<\/jats:p>","DOI":"10.1007\/s10846-025-02341-1","type":"journal-article","created":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T12:48:06Z","timestamp":1765284486000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Intelligent Framework for Human-Robot Collaboration: Dynamic Ergonomics and Adaptive Decision-Making"],"prefix":"10.1007","volume":"112","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5918-2422","authenticated-orcid":false,"given":"Francesco","family":"Iodice","sequence":"first","affiliation":[]},{"given":"Elena","family":"De\u00a0Momi","sequence":"additional","affiliation":[]},{"given":"Arash","family":"Ajoudani","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,12,9]]},"reference":[{"issue":"1","key":"2341_CR1","first-page":"151","volume":"19","author":"N Pedrocchi","year":"2013","unstructured":"Pedrocchi, N., Vicentini, F., Tosatti, A., Molinari-Tosatti, L.: Safe human-robot cooperation in an industrial environment. 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