Teaching Industrial Robotics with AI and XR
The increasing adoption of automation across industrial sectors calls for innovative educational approaches that prepare learners for human–robot collaboration. However, traditional training methods involving the usage of robots on real equipment remain limited by high costs, safety concerns, and restricted access to authentic industrial settings. The TI-RAX (Teach Industrial Robotics with AI and XR) project addresses these challenges by leveraging artificial intelligence and extended reality to create immersive, interactive, and scalable training scenarios focused on human–robot collaboration within industrial settings.
Technology
Through an intelligent, multi-agent environment, instructors can iteratively refine training plans and materials with the assistance of virtual agents and simulated learners based on artificial intelligence models, who question, challenge, and test content prior to actual use. Building upon the eXRecise text-to-scenario generation tool, the resulting training activities are deployed on the VIROO platform as extended reality scenarios and delivered to real learners within the MASTER-XR ecosystem.
Two use cases (handling automotive batteries and dismantling refrigerators) operationalize this vision, allowing learners with no prior expertise to collaborate with robots on representative industrial tasks. We expect that TI-RAX will help democratize access to industrial robotics education, advance instructional design through intelligent feedback mechanisms, and establish the groundwork for the commercial adoption of customizable, high-quality training solutions that foster human–robot collaboration in modern industry.
