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Autobrik/tangram-square-rectangle-house-panda-300ep

This dataset was created using LeRobot. Dataset Description Demonstrations for Tangram-Bench: a Panda arm in MuJoCo assembles a tangram silhouette from a packed square of seven pieces, given the silhouette outline on the table and a one-sentence prompt. Episodes 300 (300 solved) Distinct scenes 300; the designed grid holds 7,776 per figure, seed n + 7776 repeating seed n Frames 616,513 at 10 fps, 1028 min of manipulation Figures square, rectangle, house… See the full description on the dataset page: https://huggingface.co/datasets/Autobrik/tangram-square-rectangle-house-panda-300ep.

sourceHugging Facemitupdated 13d agoView on Hugging Face
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Dataset Card

This dataset was created using LeRobot.

<a class="flex" href="https://huggingface.co/spaces/lerobot/visualize_dataset?path=murobotics/tangram-square-rectangle-house-panda-300ep"> <img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl.svg"/> <img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl-dark.svg"/> </a>

Dataset Description

Demonstrations for Tangram-Bench: a Panda arm in MuJoCo assembles a tangram silhouette from a packed square of seven pieces, given the silhouette outline on the table and a one-sentence prompt.

Episodes300 (300 solved)
Distinct scenes300; the designed grid holds 7,776 per figure, seed n + 7776 repeating seed n
Frames616,513 at 10 fps, 1028 min of manipulation
Figuressquare, rectangle, house
Robotpanda, simulated (MuJoCo)
Camerasobservation.images.top, observation.images.wrist, 320x240
Stateobservation.state: 7 arm joints and 2 finger joints, rad and m
Actionaction: 7 joint targets in rad and a gripper command, 1 open, 0 closed
Taskthe figure prompt
Demonstratorthe repository's reference controller, one seed per episode
FigureEpisodesSolvedPrompt
square100100Solve the tangram puzzle to assemble the square.
rectangle100100Solve the tangram puzzle to assemble the rectangle.
house100100Solve the tangram puzzle to assemble the house.

How the episodes were recorded

Scenes come from the benchmark's designed grid: goal yaw every 30 degrees, packed square yaw every 45 degrees, centres offset by up to 30 mm, all inside the arm's workspace. A seed fixes the scene and the demonstrator, so any episode reproduces exactly with tools.collect in the repository; episodes.jsonl maps each episode index to its seed, figure, success, prompt, plan and subtask segments. An episode ends four seconds after the benchmark's success test has held, once the arm has returned home.

Language annotations

language_persistent carries the demonstrator's numbered plan (refreshed at every step) and the subtask sentence in progress, in the layout lerobot-annotate writes; language_events is empty.

  • —Homepage: https://github.com/murobotics-ai/tangram-bench
  • —Paper: [More Information Needed]
  • —License: mit

Dataset Structure

meta/info.json:

json
{
    "codebase_version": "v3.0",
    "fps": 10,
    "features": {
        "observation.images.top": {
            "dtype": "video",
            "shape": [
                240,
                320,
                3
            ],
            "names": [
                "height",
                "width",
                "channels"
            ],
            "info": {
                "video.height": 240,
                "video.width": 320,
                "video.codec": "av1",
                "video.pix_fmt": "yuv420p",
                "video.fps": 10,
                "video.channels": 3,
                "has_audio": false,
                "video.g": 2,
                "video.crf": 30,
                "video.preset": 12,
                "video.fast_decode": 0,
                "video.video_backend": "pyav",
                "video.extra_options": {},
                "is_depth_map": false
            }
        },
        "observation.images.wrist": {
            "dtype": "video",
            "shape": [
                240,
                320,
                3
            ],
            "names": [
                "height",
                "width",
                "channels"
            ],
            "info": {
                "video.height": 240,
                "video.width": 320,
                "video.codec": "av1",
                "video.pix_fmt": "yuv420p",
                "video.fps": 10,
                "video.channels": 3,
                "has_audio": false,
                "video.g": 2,
                "video.crf": 30,
                "video.preset": 12,
                "video.fast_decode": 0,
                "video.video_backend": "pyav",
                "video.extra_options": {},
                "is_depth_map": false
            }
        },
        "observation.state": {
            "dtype": "float32",
            "shape": [
                9
            ],
            "names": [
                "joint0",
                "joint1",
                "joint2",
                "joint3",
                "joint4",
                "joint5",
                "joint6",
                "finger0",
                "finger1"
            ]
        },
        "action": {
            "dtype": "float32",
            "shape": [
                8
            ],
            "names": [
                "joint0",
                "joint1",
                "joint2",
                "joint3",
                "joint4",
                "joint5",
                "joint6",
                "gripper"
            ]
        },
        "timestamp": {
            "dtype": "float32",
            "shape": [
                1
            ],
            "names": null
        },
        "frame_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "episode_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "task_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "language_persistent": {
            "dtype": "language",
            "shape": [
                1
            ],
            "names": null
        },
        "language_events": {
            "dtype": "language",
            "shape": [
                1
            ],
            "names": null
        }
    },
    "total_episodes": 300,
    "total_frames": 616513,
    "total_tasks": 3,
    "chunks_size": 1000,
    "data_files_size_in_mb": 100,
    "video_files_size_in_mb": 200,
    "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",
    "robot_type": "panda",
    "splits": {
        "train": "0:300"
    }
}

Citation

BibTeX:

bibtex
[More Information Needed]