Akademik Veri Yönetim Sistemi
International Conference on Educational Technology and Online Learning, Eskişehir, Türkiye, 16 Mayıs 2024
Extended Reality (XR) technology holds significant transformative potential
in the fields of education and industry, yet current training methodologies
fall short in understanding robotic systems and human-robot interaction. These
approaches often focus on theoretical knowledge while neglecting practical
application and real-world experiences, creating a gap that hinders the
workforce's effective operation with robotic systems.
The XR4HRC project, funded by the European Union’s Horizon Europe research and
innovation action program through the XR2Learn Project and conducted in
collaboration with Lider Teknoloji Geliştirme (LTG), BEST Institut für
berufsbezogene Weiterbildung und Personaltraining GmbH (BEST), and Eskişehir
Osmangazi University Smart Factory and Robotics Laboratory (IFARLAB), aims to
apply XR-based training and evaluation methods to industrial robotic systems.
The project seeks to enhance users' learning experiences and provide them with
opportunities to practice in realistic industrial scenarios. Particularly equipped
with Virtual Reality (VR) and Augmented Reality (AR) applications centered
around the operation of the Kawasaki RS005L robotic device, this approach is
aimed at improving the quality control and robotic system management skills of
both students and industry workers.
In this context, three tailored training and evaluation scenarios have been
designed: (i) Health and Safety Protocols, (ii) Orientation, and (iii) General
Maintenance of Robotic Systems. Participants will be able to complete these
training and evaluation scenarios independently, and instructors will also be
able to facilitate the remote evaluation process by sharing the same session
during the evaluation, thus enabling student evaluation through remote
collaboration.
The VR module allows users to interact with virtual robotic systems through
interactive scenarios created using the Unity platform and the INTERACT plugin,
while the AR module enhances training by visualizing virtual information in a
real laboratory environment, enriched using Meta's XR SDK. This integration
facilitates users' understanding of the physical-world counterparts of actions
performed in a virtual environment, deepening the learning process and
enhancing operational skills. Furthermore, the use of devices like the Meta
Quest 3, with its advanced processor performance and high-quality sensor
capacity, maximizes the efficiency and interactive experience of such training
scenarios. The XR4HRC project supports Europe's Industry 5.0 vision by
advancing training and evaluation methodologies in the fields of extended
reality and human-robot collaboration.