---
license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- robotics
- lerobot
- manipulation
- isaac-lab
- data-generation
- MimicGen
configs:
- config_name: default
  data_files: data/*/*.parquet
---

This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).

## Dataset Description

Simulated manipulation demonstrations generated by our **MimicGen** reimplementation on the RoboLab
(Isaac Lab) benchmark. One of 12 cells in a generator x task x difficulty grid.

## What this is

| | |
|---|---|
| Generator | MimicGen (our reimplementation, not the authors' code) |
| Task | `banana` |
| Initial-pose randomization | `medium` — position 50%, yaw ±25° |
| Episodes | 3039 (successes only) |
| Generation success rate | 0.279 |

## Action convention — read this before training

Actions are **absolute joint targets in the DROID frame** (arm 7-DoF with the j7 mount offset
applied) plus a **binary gripper in {0, 1}**. They are *not* deltas. Applying a delta transform on
top will silently produce a different controller.

The binary gripper matters: a continuous gripper channel **overestimates** downstream policy
performance in our measurements, so it is binarized at collection time.

## How the data was produced

Source demos (pi05 policy rollouts) -> **MimicGen** (object-centric SE(3) retargeting) -> for PGDG
cells, those MimicGen episodes are in turn the source for the control-point sampler. Every episode
is rolled out in physics and only successes are stored, so the *generation success rate* above is
also the cost driver: episodes that fail consume the same simulation budget as ones that succeed.

Difficulty levels randomize the object's initial placement: position as a fraction of the task's
feasible radius, and yaw as a half-angle.

## Caveats

- **Only successful episodes are included.** Failure modes are not represented here.
- Success is defined by a K-step settle (hold) criterion in the environment, not a single frame.
- Observations are two cameras (over-shoulder + wrist) at 270x480, 15 fps, plus proprioceptive state.
- Quantile statistics (q01/q99) are precomputed, and videos are re-encoded to constant frame rate
  so that torchcodec-based dataloaders work.
- This is **our reimplementation** of the published methods, not the original authors' code. Several
  hyperparameters are not specified in the papers and were chosen by us.
## Visualize

[Open in the LeRobot dataset visualizer](https://huggingface.co/spaces/lerobot/visualize_dataset?dataset=DAVIAN-Robotics/robolab-mg-banana-medium&episode=0)


- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0

## Dataset Structure

[meta/info.json](meta/info.json):
```json
{
    "codebase_version": "v3.0",
    "robot_type": "unknown",
    "total_episodes": 3039,
    "total_frames": 692970,
    "total_tasks": 1,
    "chunks_size": 1000,
    "data_files_size_in_mb": 100,
    "video_files_size_in_mb": 200,
    "fps": 15,
    "splits": {
        "train": "0:3039"
    },
    "data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
    "video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
    "features": {
        "action": {
            "dtype": "float32",
            "shape": [
                8
            ],
            "names": {
                "motors": [
                    "j0",
                    "j1",
                    "j2",
                    "j3",
                    "j4",
                    "j5",
                    "j6",
                    "gripper"
                ]
            },
            "fps": 15
        },
        "observation.state": {
            "dtype": "float32",
            "shape": [
                8
            ],
            "names": {
                "motors": [
                    "joint_0",
                    "joint_1",
                    "joint_2",
                    "joint_3",
                    "joint_4",
                    "joint_5",
                    "joint_6",
                    "joint_7"
                ]
            },
            "fps": 15
        },
        "observation.velocity": {
            "dtype": "float32",
            "shape": [
                8
            ],
            "names": null,
            "fps": 15
        },
        "episode_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "frame_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "task_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "timestamp": {
            "dtype": "float32",
            "shape": [
                1
            ],
            "names": null
        },
        "next.done": {
            "dtype": "bool",
            "shape": [
                1
            ],
            "names": null,
            "fps": 15
        },
        "observation.images.over_shoulder_left_camera": {
            "dtype": "video",
            "shape": [
                270,
                480,
                3
            ],
            "names": [
                "height",
                "width",
                "channels"
            ],
            "info": {
                "video.height": 270,
                "video.width": 480,
                "video.codec": "avc1",
                "video.pix_fmt": "yuv420p",
                "video.is_depth_map": false,
                "video.fps": 15.0,
                "video.channels": 3,
                "has_audio": false
            }
        },
        "observation.images.wrist_cam": {
            "dtype": "video",
            "shape": [
                270,
                480,
                3
            ],
            "names": [
                "height",
                "width",
                "channels"
            ],
            "info": {
                "video.height": 270,
                "video.width": 480,
                "video.codec": "avc1",
                "video.pix_fmt": "yuv420p",
                "video.is_depth_map": false,
                "video.fps": 15.0,
                "video.channels": 3,
                "has_audio": false
            }
        }
    }
}
```


## Citation

**BibTeX:**

```bibtex
[More Information Needed]
```