UD77/latchbench-so101-v0

LatchBench SO-101 RJ45 insertion, v0

Simulated demonstrations of an SO-101 arm inserting an RJ45 plug into a 3-port network switch, recorded in LatchBench (Isaac Lab-Arena, PhysX) and stored in LeRobot v3 format with the real SO-101 conventions (joint names, degrees, 30 fps).

Contents

• 600 episodes, all successful (the latch clicked): 100 per port on the loose (+0.50 mm) and medium (+0.25 mm) clearance tiers.
• Recorded from the open-loop expert, given the exact port pose. Every episode is a straight push into the port. There is no search and no reaction to contact.
• observation.state holds the 6 joint positions in degrees. action holds the 6 joint goal positions in degrees.
• observation.images.front and observation.images.wrist: 480x640 video.
• observation.servo_load and observation.servo_current: the simulated STS3215 Present_Load (signed, 0.1 % PWM duty per count) and Present_Current (6.5 mA per count) registers, decoded the way LeRobot reads them on a real arm (servosense).
• task: "insert the cable into the left / middle / right port".
• meta/latchbench_episodes.jsonl: tier, port, seed and raw-file index per episode.

This is the dataset behind the v0 GR00T fine-tune, which never latched (0 of 150 evaluation episodes). The demonstrations work only because the expert knew the port position exactly, so they give a policy nothing contact-driven to learn. See the GR00T section of the LatchBench README for the full story. Model: UD77/latchbench-groot-n17.

Limits: everything is simulated, the plug is rigidly attached to the gripper, and mapping these joint values to a real arm needs that arm's LeRobot calibration file.

Dataset Structure

meta/info.json:

{
    "codebase_version": "v3.0",
    "fps": 30,
    "features": {
        "observation.state": {
            "dtype": "float32",
            "shape": [
                6
            ],
            "names": [
                "shoulder_pan.pos",
                "shoulder_lift.pos",
                "elbow_flex.pos",
                "wrist_flex.pos",
                "wrist_roll.pos",
                "gripper.pos"
            ]
        },
        "action": {
            "dtype": "float32",
            "shape": [
                6
            ],
            "names": [
                "shoulder_pan.pos",
                "shoulder_lift.pos",
                "elbow_flex.pos",
                "wrist_flex.pos",
                "wrist_roll.pos",
                "gripper.pos"
            ]
        },
        "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": 30,
                "video.channels": 3,
                "has_audio": false,
                "video.g": 2,
                "video.crf": 30,
                "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",
                "video.pix_fmt": "yuv420p",
                "video.fps": 30,
                "video.channels": 3,
                "has_audio": false,
                "video.g": 2,
                "video.crf": 30,
                "video.preset": null,
                "video.fast_decode": 0,
                "video.video_backend": "pyav",
                "video.extra_options": {},
                "is_depth_map": false
            }
        },
        "observation.servo_load": {
            "dtype": "int32",
            "shape": [
                6
            ],
            "names": [
                "shoulder_pan.load",
                "shoulder_lift.load",
                "elbow_flex.load",
                "wrist_flex.load",
                "wrist_roll.load",
                "gripper.load"
            ]
        },
        "observation.servo_current": {
            "dtype": "int32",
            "shape": [
                6
            ],
            "names": [
                "shoulder_pan.current",
                "shoulder_lift.current",
                "elbow_flex.current",
                "wrist_flex.current",
                "wrist_roll.current",
                "gripper.current"
            ]
        },
        "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
        }
    },
    "total_episodes": 600,
    "total_frames": 94848,
    "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": "so101_follower",
    "splits": {
        "train": "0:600"
    }
}

Citation

If you use this dataset, please cite the LatchBench repository: https://github.com/UD-Y/latchbench