Year: 2025
Type: article
Abstract: This letter introduces Robotic Augmented Reality for Machine Programming by Demonstration (Rampa), the first ML-integrated, XR-driven end-to-end robotic system, allowing training and deployment of ML models such as ProMPs on the fly, and utilizing the capabilities of state-of-the-art and commercially available AR headsets, e.g.,Meta Quest 3, to facilitate the application of Programming by Demonstration (PbD) approaches on industrial robotic arms, e.g.,Universal Robots UR10. Our approach enablesin-situdata recording, visualization, and fine-tuning of skill demonstrations directly within the user's physical environment.Rampaaddresses critical challenges of PbD, such as safety concerns, programming barriers, and the inefficiency of collecting demonstrations on the actual hardware. The performance of our system is evaluated against the traditional method of kinesthetic control in teaching three different robotic manipulation tasks and analyzed with quantitative metrics, measuring task performance and completion time, trajectory smoothness, system usability, user experience, and task load using standardized surveys. Our findings indicate a substantial advancement in how robotic tasks are taught and refined, promising improvements in operational safety, efficiency, and user engagement in robotic programming.
Institutions: Boğaziçi University, Adobe Systems (United States)
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
Funder: European Commission
OpenAlex ID: W4407948459