kshitiz25/real_world_packing_task

Bimanual xArm Packing (Real World)

Teleoperated demonstrations of a bimanual packing task on two real xArm robots. The arms pack household objects (for example a sponge, a Cheez-It container and an Altoids container) into small, medium and large boxes. Each episode is one subtask, such as "Pack Sponge into medium box.", and the task field holds that instruction. Instruction wording varies across episodes (for example with and without "the"), as recorded during collection.

Layout

Each round folder is a complete LeRobot dataset (codebase version 2.1).

Folder	Episodes	Frames
baseline/round1	164	97,522
baseline/round2	282	167,612
baseline/round3	283	147,111
baseline/round4	281	157,816
baseline/round5	280	154,808
baseline/round6	282	151,189
beta-data/round1	566	331,819
beta-data/round2	653	351,865
beta-data/round3	626	344,594

baseline holds standard demonstrations. beta-data holds demonstrations collected while a person perturbs the scene during the task, so episodes include recovery from disturbed states, and that person is often visible in the camera views.

Features

All rounds share one schema, which matches the simulation dataset kshitiz25/sim_packing_task, and are recorded at 60 Hz.

Key	Shape	Description
observation.state	float32 (20,)	Per arm, left then right: end-effector position (x, y, z), rotation as the first two columns of the rotation matrix (r00, r10, r20, r01, r11, r21), gripper
action	float32 (20,)	Target pose in the same 20-d layout as the state
observation.images.base	video, 3x224x224	Overhead camera
observation.images.left_wrist	video, 3x224x224	Left wrist camera
observation.images.right_wrist	video, 3x224x224	Right wrist camera
task_index	int64	Index into meta/tasks.jsonl

Videos are AV1-encoded MP4 files; decoding them needs an FFmpeg build with an AV1 decoder (for example libdav1d). meta/high_level_prompts.json stores the goal-level prompt for each episode.

Usage

Download one round and read its frames:

from huggingface_hub import snapshot_download
import pandas as pd

root = snapshot_download(
    "kshitiz25/real_world_packing_task",
    repo_type="dataset",
    allow_patterns="baseline/round1/*",
)
ds_root = f"{root}/baseline/round1"
frames = pd.read_parquet(f"{ds_root}/data/chunk-000/episode_000000.parquet")

Point a LeRobot release that reads codebase version 2.1 at ds_root to load a round as a LeRobotDataset.