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The integration of Augmented Reality (AR) into Human–Robot Interaction (HRI) represents a significant advancement in collaborative technologies. This paper provides a comprehensive review of AR applications within HRI with a focus on manufacturing, emphasizing their role in enhancing collaboration, trust, and safety. By aggregating findings from numerous studies, this research highlights key challenges, including the need for improved Situational Awareness, enhanced safety, and more effective communication between humans and robots. A framework developed from the literature is presented, detailing the critical elements of AR necessary for advancing HRI. The framework outlines effective methods for continuously evaluating AR systems for HRI. The framework is supported with the help of two case studies and another ongoing research endeavor presented in this paper. This structured approach focuses on enhancing collaboration and safety, with a strong emphasis on integrating best practices from Human–Computer Interaction (HCI) centered around user experience and design. 

While human safety is always a concern in an environment with human-robot collaboration, this concern magnifies when it is the human-robot work-space that overlaps. This overlap creates potential for collision which would reduce the safety of the system. Fear of such a collision could reduce the productivity of the system. This apprehensiveness is referred to as the perceived safety of the robot by the human. Therefore, we designed a within-subject human-robot collaboration experiment where a human and a robot work together in an assembling task. In order to evaluate the perceived safety during this HRC task, we collected subjective data by means of a questionnaire through two methods: during and after trial. The collected data was analyzed using non-parametric methods and these statistical tests were conducted: Friedman and Wilcoxon. The most clear relationship was found when changing only sensitivity of the robot or all three behaviors of velocity, trajectory, and sensitivity. There is a positive moderate linear relationship between the average safety of the during trial data and the after trial data.