Mixed Reality for Human–Robot Teaming to Enhance Work Health and Safety in Manufacturing Industries: A Systematic Literature Review

Abstract

Abstract Mixed reality (MR) integrated with human–robot teaming (HRT) has emerged as a promising approach to address persistent challenges in work health and safety (WHS) within manufacturing. To evaluate its potential, we conducted a systematic review of 33 peer-reviewed studies published between 2015 and 2024, identified from databases indexed in Google Scholar (e.g., IEEE, Elsevier, Springer, MDPI). Studies were screened using predefined inclusion and exclusion criteria, and quality was appraised with the Mixed-Methods Appraisal Tool (MMAT). The synthesis highlights three major applications of MR in HRT for WHS: immersive training and ergonomic assessment, real-time hazard monitoring and visualization, and enhanced human–robot communication via intuitive interfaces and natural language processing. Reported benefits include faster skill acquisition, improved situational awareness, and reduced accident risks. However, key barriers remain—particularly cognitive overload, ergonomic discomfort, integration with legacy manufacturing systems, and limited longitudinal evidence. Despite these challenges, the review demonstrates that MR–HRT solutions can significantly strengthen WHS outcomes if designed with ergonomic validation, adaptive feedback mechanisms, and scalable deployment strategies. For manufacturing industries, the findings provide a practical roadmap: prioritize user-centered MR design, invest in real-world pilot implementations, and embed WHS outcomes into technology evaluation. Advancing MR–HRT beyond proof-of-concept will require interdisciplinary collaboration and rigorous validation, enabling safer, smarter, and more resilient manufacturing environments.