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RoboAct: Robot Action Learning Framework
📑 Paper | 🌐 Project Page | 💾 Released Resources | 📦 Repo
We release the raw data for our processed Motion dataset, adopted from the original RT-X (Open X-Embodiment) dataset from Google DeepMind team.
The data format for each line in the robot_motion_sequences.jsonl is as follows:
{
"episode_id": <unique identifier for the episode>,
"robot_type": <robot platform used for data collection>,
"task_description": <natural language task instruction>,
"observation_space": {
"image_primary": <path to primary camera image>,
"image_wrist": <path to wrist camera image>,
"state": <robot proprioceptive state vector>
},
"action_sequence": [
{
"action": <7-DoF action vector>,
"timestamp": <action timestamp>
},
...
],
"source": <original RT-X dataset subset>,
"difficulty": <easy/medium/hard>,
"meta": <additional metadata>
}
Some of the action_sequence entries are incomplete due to episode truncation during collection. These are marked in the metadata.
*Note: Due to the heterogeneous nature of robotics data from multiple labs, some action spaces have been normalized to a common format. Original action definitions are preserved in the metadata.
License
The license for this dataset is CC-BY-4.0.
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