What Is Robot Training Data and How to Collect It
Robot training data is the raw material that makes modern robotic AI possible. Without high-quality demonstrations, imitation learning models cannot generalize, and VLA systems cannot achieve reliable real-world performance. Here is what you need to know before starting a data collection program.
What Is Robot Training Data?
Robot training data consists of recorded demonstrations of a robot performing tasks — capturing joint positions, end-effector poses, camera images, force/torque readings, and operator control inputs in synchronized timestamped streams. This data is used to train imitation learning policies, fine-tune vision-language-action (VLA) models, and build reward functions for reinforcement learning. SVRC's data services handle end-to-end collection, annotation, and export for research and commercial teams.
Why Data Quality Matters More Than Quantity
A common misconception is that more demonstrations always produce better models. In practice, data diversity — varied object positions, lighting conditions, and operator strategies — matters far more than sheer episode count. Noisy or inconsistent demonstrations actively harm policy performance. SVRC's collection protocols enforce consistency checks, retake criteria, and multi-camera coverage standards to ensure every episode meets a defined quality bar before it enters a dataset.
Teleoperation vs Kinesthetic Teaching vs Scripted Collection
Three main methods are used to collect robot demonstrations. Teleoperation — using a control interface to operate the robot in real time — produces the most natural and generalizable data. Kinesthetic teaching physically guides the robot arm through motions and records the trajectory. Scripted collection runs predefined motion primitives to generate high-volume data for well-defined subtasks. Most production datasets combine all three depending on the task complexity and required diversity.
What Hardware Do You Need?
At minimum, a data collection setup requires a robot arm or mobile platform, one or more RGB cameras (wrist-mounted and overhead), a teleoperation controller or glove, and a logging system that synchronizes all streams. SVRC's leased hardware packages include preconfigured data collection setups for the OpenArm, Mobile ALOHA, and other platforms, so teams can start collecting on day one without building custom infrastructure.
Data Formats, Annotation, and Export
Raw collected data is typically stored as HDF5 or zarr files with synchronized observation and action streams. Annotation layers — task segmentation, success flags, language instruction labels — are added during post-processing. SVRC exports to formats compatible with LeRobot, Lerobot HF datasets, Open X-Embodiment, and custom policy training pipelines. Browse existing public datasets to understand the data structure before designing your own collection.
How to Start a Data Collection Program with SVRC
The fastest path is to contact the Data Services team with your task description, target robot platform, and desired episode count. SVRC provides collection operators, hardware, a controlled lab environment in Palo Alto, and the full post-processing pipeline. Remote collection using SVRC-leased hardware at your facility is also supported for tasks that require your specific environment or objects.