AIRSPEED: An Open Source Data Production Platform for Embodied Artificial Intelligence
Abstract
The development of embodied AI (EAI) critically depends on efficient data acquisition, yet faces persistent challenges including high costs, limited training scenarios, and lack of standardized datasets. We present AIRSPEED, an open source data production platform designed to address these bottlenecks through three core innovations. First, AIRSPEED achieves hardware–software decoupling via unified robot and simulation interfaces, enabling seamless integration with diverse data collection devices and simulation platforms. Second, it supports comprehensive data production methods spanning teleoperation and teaching approaches, as well as synthetic data generation through data synthesis and virtual teleoperation. Third, AIRSPEED automates pyramid-structured dataset construction compatible with both HDF5 and LeRobot formats, significantly reducing manual overhead. Experimental validation demonstrates substantial efficiency gains, achieving up to 35.6× acceleration in dataset construction and 6.0× overall speedup compared to manual workflows. With end-to-end latency as low as 3 ms and compression throughput exceeding 296 MB/s, AIRSPEED establishes a scalable foundation for EAI data production. AISPEED is open sourced on this website: URL .
Fields of Study & Subjects
Human Motion and Animation
Social Robot Interaction and HRI
Robot Manipulation and Learning
Publication details
- Journal / source
- ACM Transactions on Cyber-Physical Systems
- Publisher
- Association for Computing Machinery (ACM)
- Volume
- 10
- Issue
- 3
- Pages
- 1–22
- Publication date
- 8 April 2026
- Language
- EN