Effectiveness of VR-based training on improving construction workers’ knowledge, skills, and safety behavior in robotic teleoperation

The emergence of construction robotics and automation has produced an urgent and vast need for construction workers to reskill and upskill for the future of work. Virtual Reality (VR)-based training has been considered and investigated as a safe and cost-effective training method that allows workers to be exposed to hazardous tasks with negligible actual safety risks in comparison to existing training methods (hands-on, lecture-based, apprenticeship training). This paper aims to investigate the impact of VR-based training on construction workers’ knowledge acquisition, operational skills, and safety behavior during robotic teleoperation compared to the traditional in-person training method. Fifty construction workers were randomly assigned to complete either VR-based or in-person training for operating a demolition robot. We used quantitative and qualitative data analyses to answer our research questions. Our results indicate that VR-based training was associated with a significant increase in knowledge, operational skills, and safety behavior compared to in-person training. Our findings suggest that VR-based training not only provides a viable and effective option for future training programs but a valuable option for construction robotics safety and skill training

A Multidimensional Taxonomy for Human-Robot Interaction in Construction

Despite the increased interest in construction robotics both in academia and the industry, insufficient attention has been given to aspects related to Human-Robot Interaction (HRI). Characterizing HRI for construction tasks can help researchers organize knowledge in a structured manner that allows for classifying construction robotics applications and comparing and benchmarking different studies. This paper builds upon existing taxonomies and empirical studies in HRI in various industries (e.g., construction, manufacturing, and military, among others) to propose a multidimensional taxonomy to characterize HRI applications in the construction industry. The taxonomy design followed a systematic literature review in which common themes were identified and grouped into 16 categories. The proposed taxonomy can be used as a foundation for systematic reviews and meta-analyses of HRI applications in construction and can benefit the construction industry by informing the design of collaborative tasks performed by human-robot teams