ARMADA: Augmented Reality for Robot Manipulation and Robot-Free Data Acquisition
On the map: Offline RL and imitation learning from data → Robot manipulation imitation learning
Abstract (arXiv)
Teleoperation for robot imitation learning is bottlenecked by hardware availability. Can high-quality robot data be collected without a physical robot? We present a system for augmenting Apple Vision Pro with real-time virtual robot feedback. By providing users with an intuitive understanding of how their actions translate to robot motions, we enable the collection of natural barehanded human data that is compatible with the limitations of physical robot hardware. We conducted a user study with 15 participants demonstrating 3 different tasks each under 3 different feedback conditions and directly replayed the collected trajectories on physical robot hardware. Results suggest live robot feedback dramatically improves the quality of the collected data, suggesting a new avenue for scalable human data collection without access to robot hardware. Videos and more are available at https://nataliya.dev/armada.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Placed in Robot manipulation imitation learning, one of 13 directions in Offline RL and imitation learning from data. First posted on arXiv 14 Dec 2024.
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Citing papers per year: 2025: 3; 2026: 1.
4 papers.
- 2025EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Videocited by 211
- 2025Physics-Driven Data Generation for Contact-Rich Manipulation via Trajectory Optimizationcited by 21
- 2025IRIS: An Immersive Robot Interaction Systemcited by 2
- 2026Touch2Robot: Robot Touch in the Human Demonstration Loopcited by 0
- 2026Touch2Robot: Robot Touch in the Human Demonstration Loop21 Sep 2026
- 2025EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video16 May 2025
- 2025Physics-Driven Data Generation for Contact-Rich Manipulation via Trajectory Optimization27 Feb 2025
- 2025IRIS: An Immersive Robot Interaction System5 Feb 2025
Similar, not cited
Close in wording, no citation either way
- 2024ARCap: Collecting High-quality Human Demonstrations for Robot Learning with Augmented Reality Feedback
- 2024Augmented Reality Demonstrations for Scalable Robot Imitation Learning
- 2025ARMimic: Learning Robotic Manipulation from Passive Human Demonstrations in Augmented Reality
- 2024ARCADE: Scalable Demonstration Collection and Generation via Augmented Reality for Imitation Learning
- 2025dARt Vinci: Egocentric Data Collection for Surgical Robot Learning at Scale
- 2026RoboPaint: From Human Demonstration to Any Robot and Any View
- 2022Leveraging Haptic Feedback to Improve Data Quality and Quantity for Deep Imitation Learning Models
- 2024TelePreview: A User-Friendly Teleoperation System with Virtual Arm Assistance for Enhanced Effectiveness ↗