Abstract
As industrial robotics increasingly enters creative and design domains, there is a growing need for educational platforms that support training in industrial robot control, planning, and system configuration. Existing training systems often assume that learners have knowledge of code-based robotics programming, which limits accessibility to creative practitioners. This paper presents the Augmented Reality-based Interactive Robotic Training Platform (AR-IRTP), which reinterprets core industrial robotics concepts, such as tool selection, workspace setup and motion planning, through embodied AR interaction. The platform is based on the Robotic Induction course from the DMaF Robotic Lab and structured using the Human-Robot Leader-Follower (HRLF) model to scaffold the learning flow through a two-phase interaction sequence: configuration and execution. We conducted a mixed-methods study with 30 participants from fabrication, design and human-computer interaction (HCI) backgrounds to evaluate how AR-IRTP supports understanding, interaction fluency, trust, and operational safety. The results show that the AR interface effectively reduces cognitive and technical barriers, enabling novices to grasp abstract robotic principles through intuitive, spatial interaction.
Keywords
Augmented Reality (AR); Human-robot Collaboration (HRC); Industrial Robotics in Education; Embodied Interaction
DOI
https://doi.org/10.21606/iasdr.2025.79
Citation
Zhao, Y., Masuda, L., Liu, Z., Reinhardt, D.,and Loke, L.(2025) Learning Robot Control through Co-Drawing: An Augmented Reality-based Interactive Robotic Training Platform for Building Foundational Knowledge in Industrial Robotics, in Chang, C.-Y., and Hsu, Y. (eds.), IASDR 2025: Design Next, 02-05 December, Taiwan. https://doi.org/10.21606/iasdr.2025.79
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Track 12 - Design Education
Learning Robot Control through Co-Drawing: An Augmented Reality-based Interactive Robotic Training Platform for Building Foundational Knowledge in Industrial Robotics
As industrial robotics increasingly enters creative and design domains, there is a growing need for educational platforms that support training in industrial robot control, planning, and system configuration. Existing training systems often assume that learners have knowledge of code-based robotics programming, which limits accessibility to creative practitioners. This paper presents the Augmented Reality-based Interactive Robotic Training Platform (AR-IRTP), which reinterprets core industrial robotics concepts, such as tool selection, workspace setup and motion planning, through embodied AR interaction. The platform is based on the Robotic Induction course from the DMaF Robotic Lab and structured using the Human-Robot Leader-Follower (HRLF) model to scaffold the learning flow through a two-phase interaction sequence: configuration and execution. We conducted a mixed-methods study with 30 participants from fabrication, design and human-computer interaction (HCI) backgrounds to evaluate how AR-IRTP supports understanding, interaction fluency, trust, and operational safety. The results show that the AR interface effectively reduces cognitive and technical barriers, enabling novices to grasp abstract robotic principles through intuitive, spatial interaction.