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EmbodiedSWE/clear_organic_agent_ab_A400.jointtarget_20hz_20260918

This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.front": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/EmbodiedSWE/clear_organic_agent_ab_A400.jointtarget_20hz_20260918.

sourceHugging Faceapache-2.0updated 8d 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/visualizedataset?path=CoSiGen/clearorganicagentabA400.jointtarget20hz_20260918"> <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

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

Dataset Structure

meta/info.json:

json
{
    "codebase_version": "v3.0",
    "fps": 20,
    "features": {
        "observation.images.front": {
            "dtype": "video",
            "shape": [
                480,
                640,
                3
            ],
            "names": [
                "height",
                "width",
                "channels"
            ],
            "info": {
                "video.height": 480,
                "video.width": 640,
                "video.codec": "h264",
                "video.pix_fmt": "yuv420p",
                "video.fps": 20,
                "video.channels": 3,
                "has_audio": false,
                "video.g": 5,
                "video.crf": 23,
                "video.preset": null,
                "video.fast_decode": 0,
                "video.video_backend": "pyav",
                "video.extra_options": {},
                "is_depth_map": false
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        },
        "observation.images.side": {
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            "shape": [
                480,
                640,
                3
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            "names": [
                "height",
                "width",
                "channels"
            ],
            "info": {
                "video.height": 480,
                "video.width": 640,
                "video.codec": "h264",
                "video.pix_fmt": "yuv420p",
                "video.fps": 20,
                "video.channels": 3,
                "has_audio": false,
                "video.g": 5,
                "video.crf": 23,
                "video.preset": null,
                "video.fast_decode": 0,
                "video.video_backend": "pyav",
                "video.extra_options": {},
                "is_depth_map": false
            }
        },
        "observation.images.wrist": {
            "dtype": "video",
            "shape": [
                480,
                640,
                3
            ],
            "names": [
                "height",
                "width",
                "channels"
            ],
            "info": {
                "video.height": 480,
                "video.width": 640,
                "video.codec": "h264",
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                "video.fps": 20,
                "video.channels": 3,
                "has_audio": false,
                "video.g": 5,
                "video.crf": 23,
                "video.preset": null,
                "video.fast_decode": 0,
                "video.video_backend": "pyav",
                "video.extra_options": {},
                "is_depth_map": false
            }
        },
        "observation.state": {
            "dtype": "float32",
            "shape": [
                8
            ],
            "names": [
                "panda_joint1",
                "panda_joint2",
                "panda_joint3",
                "panda_joint4",
                "panda_joint5",
                "panda_joint6",
                "panda_joint7",
                "gripper"
            ]
        },
        "action": {
            "dtype": "float32",
            "shape": [
                8
            ],
            "names": [
                "panda_joint1_target",
                "panda_joint2_target",
                "panda_joint3_target",
                "panda_joint4_target",
                "panda_joint5_target",
                "panda_joint6_target",
                "panda_joint7_target",
                "gripper"
            ]
        },
        "raw_command": {
            "dtype": "float32",
            "shape": [
                9
            ],
            "names": [
                "cmd_0",
                "cmd_1",
                "cmd_2",
                "cmd_3",
                "cmd_4",
                "cmd_5",
                "cmd_6",
                "cmd_7",
                "cmd_8"
            ]
        },
        "timestamp": {
            "dtype": "float32",
            "shape": [
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            "names": null
        },
        "frame_index": {
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            "names": null
        },
        "episode_index": {
            "dtype": "int64",
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            "names": null
        },
        "index": {
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            "names": null
        },
        "task_index": {
            "dtype": "int64",
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            ],
            "names": null
        }
    },
    "total_episodes": 400,
    "total_frames": 849244,
    "total_tasks": 1,
    "chunks_size": 1000,
    "data_files_size_in_mb": 100,
    "video_files_size_in_mb": 42,
    "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": "packing.clear_organic_objects.franka.joint",
    "splits": {
        "train": "0:400"
    }
}

Citation

BibTeX:

bibtex
[More Information Needed]

About this dataset (agent-in-the-loop A/B, arm A, first 400 verified successes)

Simulated Franka Panda demonstrations of a produce-clearing task (pick every organic item - lemons, a lime, an orange, a small pumpkin - off a cluttered packing table and drop it into the crate, leaving the distractors), generated in Isaac Sim by the CoSiGen data-generation pipeline. Every episode is a certified success of the task grader (all present organics in the crate, no distractor in it). Grasps are real friction pinches (no weld).

  • —A/B arm A: NO agent: the delivered oracle re-run with scripted executed-action noise (gaussian 0.02 rad on the 7 arm targets, 0.4 s bursts at p=0.03 per 20 Hz step, only while the hand is above 0.85 m, i.e. transport phases) plus per-episode produce friction (0.90-1.30 / 0.80-1.10) and organic mass (x0.7-1.3) draws. Labels are the clean commands; the noise is executed below the recorder. Held out from every training scene: pomegranate01 and orange01 (the novel-object test items). Design and chronicle: experiments/2026-09-18clearorganicagent_ab/README.md in the CoSiGen repo.
  • —Episodes / frames: 400 / 849,244 at 20 Hz (11.8 h)
  • —Cameras: front, side, wrist - 480x640, h264
  • —State (8): panda_joint1..7 measured positions (rad) + gripper closedness in [0, 1] (0 = open)
  • —Action (8): ABSOLUTE panda_joint1..7_target (rad) latched at 20 Hz + commanded gripper closedness.
  • —Control law: stationary - the scene's stock Franka joint PD (kp 400 / kd 80) and gripper drives; deploy through the plain 20 Hz joint-target executor (meta/bake.json -> controller).
  • —Layout randomization: organic subset 4-5 of 5, in-group slot shuffle, +-2.5 cm jitter, free yaw; Halton draws with the solve index offset by 4093 from the physical index (independent friction and expert-parameter draws).
  • —Idle filter: stationary ticks dropped at bake time (0).
  • —Extra column: raw_command (9) - the raw controller command vector, not a policy input.