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shailes-h/yam_bimanual_manipulation

YAM Bimanual Manipulation Real-robot demonstrations for three bimanual manipulation tasks, collected on a YAM dual-arm platform and stored in LeRobot v3.0 format. Each task is a self-contained LeRobot dataset in its own top-level directory: Directory Task Episodes Frames Size blocks_filtered/ Put all blocks into the box. 97 136,489 2.3 GB dustpan_filtered/ Clean the table using the dust pan. 100 58,018 773 MB transfer_filtered/ Transfer the egg from the pan into… See the full description on the dataset page: https://huggingface.co/datasets/shailes-h/yam_bimanual_manipulation.

sourceHugging Faceapache-2.0updated 23d agoView on Hugging Face

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Dataset Card

YAM Bimanual Manipulation

Real-robot demonstrations for three bimanual manipulation tasks, collected on a YAM dual-arm platform and stored in LeRobot v3.0 format.

Each task is a self-contained LeRobot dataset in its own top-level directory:

Directory	Task	Episodes	Frames	Size
`blocks_filtered/`	Put all blocks into the box.	97	136,489	2.3 GB
`dustpan_filtered/`	Clean the table using the dust pan.	100	58,018	773 MB
`transfer_filtered/`	Transfer the egg from the pan into the bowl.	95	89,379	1.7 GB
	Total	292	283,886	4.8 GB

_filtered denotes that failed and truncated demonstrations were removed from the raw collection; every episode here runs to task completion.

Common format

All three share one recording setup:


Robot	`bi_yam_follower` (two 6-DoF arms + grippers)
Control rate	30 fps
Cameras	`top`, `left`, `right` — 480×640 RGB, AV1
Format	LeRobot `v3.0`

Features

Both an end-effector and a joint-space view of the same trajectories are stored, so the data can drive either control convention without reprocessing.

Key	Shape	Meaning
`observation.images.top`	(480, 640, 3)	Overhead camera
`observation.images.left`	(480, 640, 3)	Left wrist camera
`observation.images.right`	(480, 640, 3)	Right wrist camera
`observation.state_eef_absolute`	(16,)	Absolute EEF pose, both arms
`observation.state_joint_angles`	(14,)	Joint positions, both arms
`action_eef_absolute`	(16,)	Absolute EEF pose target
`action_eef_delta`	(16,)	EEF pose delta target
`action_joint_angles`	(14,)	Joint position target

16-D end-effector layout

Left arm at offset 0, right arm at offset 8. Each arm is:

[ x, y, z, qw, qx, qy, qz, gripper ]
    0  1  2   3   4   5   6      7

Quaternions are `w`-first (qw, qx, qy, qz), not the xyzw ordering used by SciPy and ROS — convert before feeding these into either.

14-D joint layout

Left arm at offset 0, right arm at offset 7; each arm is [joint_0 … joint_5, gripper].

Loading

Because the three datasets live in subdirectories, LeRobotDataset cannot load this repo by id alone — it expects meta/, data/ and videos/ at the root. Download the one you want, then point root at it:

python

from huggingface_hub import snapshot_download
from lerobot.datasets.lerobot_dataset import LeRobotDataset

task = "blocks_filtered"   # or dustpan_filtered / transfer_filtered

local = snapshot_download(
    repo_id="chinchinati/yam_bimanual_manipulation",
    repo_type="dataset",
    allow_patterns=f"{task}/*",
)

ds = LeRobotDataset(repo_id=task, root=f"{local}/{task}")
print(ds[0]["observation.state_eef_absolute"].shape)   # (16,)

Videos are AV1-encoded; decoding needs a build of torchcodec/ffmpeg with AV1 support.