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--- |
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size_categories: |
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- 1K<n<10K |
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viewer: false |
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--- |
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## Dataset Description |
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This is a fully annotated, synthetically generated dataset consisting of 1,000 demonstrations of a single Franka Panda robot arm performing a fixed-order three-cube stacking task in Isaac Lab. The robot consistently stacks cubes in the order: blue (bottom) → red (middle) → green (top). |
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The dataset was produced using the following pipeline: |
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- Collected 10 human teleoperation demonstrations of the stacking task. |
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- Used Isaac Lab’s **Mimic** tool to simulate 1,000 high-quality trajectories in Isaac Sim. |
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- Applied **Cosmos Transfer1** model to augment the RGB visuals from the table camera with photorealistic domain adaptation. |
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Each demonstration includes synchronized multimodal data: |
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- RGB videos from both a table-mounted and wrist-mounted camera. |
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- Depth, segmentation, and surface normal maps from the table camera. |
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- Full low-level robot and object states (joints, end-effector, gripper, cube poses). |
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- Action sequences executed by the robot. |
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This dataset is ideal for behavior cloning, policy learning, and generalist robotic manipulation research. |
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## Intended Usage |
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This dataset is intended for: |
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- Training robot manipulation policies using behavior cloning. |
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- Research in generalist robotics and task-conditioned agents. |
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- Sim-to-real transfer studies and visual domain adaptation. |
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## Dataset Characterization |
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**Data Collection Method** |
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* Human Demonstration (seed data) |
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* Synthetic Simulation (Isaac Lab Mimic) |
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* Visual Augmentation (Cosmos Transfer1) |
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10 human teleoperated demonstrations were used to bootstrap a Mimic-based simulation in Isaac Sim. All 1,000 demos are generated automatically followed by domain-randomized visual augmentation. |
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## Dataset Format |
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We provide the Mimic generated 1000 demonstrations and the 1000 Cosmos augmented demonstrations in separate HDF5 dataset files. Each demo in each file consists of a time-indexed sequence of the following modalities: |
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### Actions |
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- 7D vector: 6D relative end-effector motion + 1D gripper action |
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### Observations |
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- Robot states: Joint positions, velocities, and gripper open/close state |
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- EEF states: End-effector 6-DOF pose |
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- Cube states: Poses (positions + orientations) for blue, red, and green cubes |
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- Table camera visuals: |
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- 200×200 RGB |
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- 200×200 Depth |
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- 200×200 Segmentation mask |
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- 200×200 Surface normal map |
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- Wrist camera visuals: |
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- 200×200 RGB |
