Datasets:
license: mit
task_categories:
- robotics
- reinforcement-learning
tags:
- robotics
- world-models
- imitation-learning
- robomimic
- mimicgen
- libero
- robocasa
- dexmimicgen
- robosuite
- lance
- multi-view
size_categories:
- 1M<n<10M
robosuite + LeRobot manipulation demonstrations (Lance, 3-view)
239 manipulation datasets in the Lance format, across seven collections:
| directory | datasets | contents |
|---|---|---|
libero/ |
130 | LIBERO-130 tasks (90 + 10 + object + spatial + goal) |
robocasa/ |
65 | RoboCasa atomic kitchen tasks |
mimicgen/ |
26 | MimicGen task/level variants |
dexmimicgen/ |
9 | DexMimicGen bimanual dexterous tasks |
robomimic/ |
5 | robomimic proficient-human tasks |
ogbench/ |
2 | ogb_cube_single, ogb_scene_single |
molmo_obj_mug/ |
2 | molmo_obj_mug, molmo_obj_mug_videos |
The five replay-rendered collections hold ≈ 14.11M frames. Every dataset is
a single-version <name>.lance/ directory under its collection.
These are source demonstrations, not policy rollouts. robomimic, MimicGen, LIBERO and DexMimicGen were replayed in robosuite from recorded MuJoCo states and re-rendered to 224×224 from three camera views. RoboCasa ships as pre-rendered LeRobot videos (v0.2), so its three views are decoded directly from those videos (no replay) and resized to 224×224 for consistency.
Cameras (3 views)
Every step carries three JPEG-encoded 224×224 RGB views, in a two-exterior-plus-wrist layout:
| column | robomimic / MimicGen / LIBERO | RoboCasa | role |
|---|---|---|---|
pixels |
agentview |
robot0_agentview_left |
primary exterior |
sideview |
sideview |
robot0_agentview_right |
second exterior |
robot0_eye_in_hand |
wrist | robot0_eye_in_hand |
in-hand / eye-in-hand |
The PickPlace-family envs (mimicgen_pick_place_d0, robomimic_can) do not define
a sideview camera natively, so the standard robosuite world-level sideview is
injected at render time. All replay-rendered datasets therefore share the same
three views; RoboCasa's three come from its native left/right/wrist LeRobot videos.
Schema
All datasets share the framework columns below:
| column | type | meaning |
|---|---|---|
episode_idx |
int32 | episode index |
step_idx |
int32 | step within episode |
pixels / sideview / robot0_eye_in_hand |
binary (JPEG) | the three 224×224 RGB views |
action |
float[] | controller action (robosuite 7-dim single-arm / 14-dim bimanual; RoboCasa 12-dim) |
state |
float[] | per-step state vector |
reward |
float[1] | task reward (sparse) |
terminated / truncated / success |
float[1] | episode-end / success flags |
Replay-rendered sources (robomimic, MimicGen, LIBERO) additionally carry
qpos / qvel (MuJoCo generalized position / velocity), render_time, id,
and each source's own named low-dim observation keys, kept verbatim — e.g.
robosuite's robot0_eef_pos, object, …; LIBERO's ee_pos, ee_ori,
gripper_states, joint_states. There state is the flattened MuJoCo state used
to drive replay.
RoboCasa differs: it is derived from LeRobot recordings, not a MuJoCo replay,
so it has no qpos/qvel/sim-state. Its state is the LeRobot 16-dim
observation.state proprioception and action is the 12-dim LeRobot action.
Each source keeps its own low-dim observation names, so they vary by collection.
Datasets
robomimic — proficient-human (ph, low_dim source), re-rendered
| dataset | frames |
|---|---|
robomimic_can |
23,207 |
robomimic_lift |
9,666 |
robomimic_square |
30,154 |
robomimic_tool_hang |
95,962 |
robomimic_transport |
93,752 |
MimicGen — reset-distribution levels
| dataset | frames | dataset | frames | |
|---|---|---|---|---|
mimicgen_coffee_d0 |
223,130 | mimicgen_square_d0 |
153,477 | |
mimicgen_coffee_d1 |
224,403 | mimicgen_square_d1 |
152,400 | |
mimicgen_coffee_d2 |
224,204 | mimicgen_square_d2 |
153,112 | |
mimicgen_coffee_preparation_d0 |
689,273 | mimicgen_stack_d0 |
107,590 | |
mimicgen_coffee_preparation_d1 |
687,674 | mimicgen_stack_d1 |
108,233 | |
mimicgen_hammer_cleanup_d0 |
285,359 | mimicgen_stack_three_d0 |
254,810 | |
mimicgen_hammer_cleanup_d1 |
286,847 | mimicgen_stack_three_d1 |
255,096 | |
mimicgen_kitchen_d0 |
616,751 | mimicgen_threading_d0 |
224,508 | |
mimicgen_kitchen_d1 |
619,273 | mimicgen_threading_d1 |
223,115 | |
mimicgen_mug_cleanup_d0 |
338,136 | mimicgen_threading_d2 |
227,084 | |
mimicgen_mug_cleanup_d1 |
338,034 | mimicgen_three_piece_assembly_d0 |
336,695 | |
mimicgen_nut_assembly_d0 |
358,907 | mimicgen_three_piece_assembly_d1 |
334,869 | |
mimicgen_pick_place_d0 |
677,340 | mimicgen_three_piece_assembly_d2 |
335,949 |
The D0/D1/D2 suffix is the environment reset-distribution level, not a
data-size level. D0 initializes objects over a region resembling the source
demonstrations; D1 and D2 broaden the initial-pose distribution. See the
MimicGen dataset docs.
LIBERO — libero/ (130 tasks, 1,007,618 frames)
The LIBERO-130 lifelong-learning suite, replayed from its recorded states:
| suite | tasks | frames |
|---|---|---|
libero_10 |
10 | 138,090 |
libero_90 |
90 | 669,043 |
libero_goal |
10 | 63,728 |
libero_object |
10 | 74,507 |
libero_spatial |
10 | 62,250 |
Each task is libero/<suite>_<scene>_<language-goal>.lance.
RoboCasa — robocasa/ (65 atomic tasks, 1,495,313 frames)
RoboCasa v0.2 atomic kitchen tasks (PandaOmron mobile manipulator, procedurally generated kitchens), decoded from the released LeRobot videos:
| dataset | frames |
|---|---|
robocasa_AdjustToasterOvenTemperature |
21,328 |
robocasa_AdjustWaterTemperature |
20,953 |
robocasa_CheesyBread |
31,141 |
robocasa_CloseBlenderLid |
36,933 |
robocasa_CloseCabinet |
27,754 |
robocasa_CloseDishwasher |
15,781 |
robocasa_CloseDrawer |
15,670 |
robocasa_CloseElectricKettleLid |
7,530 |
robocasa_CloseFridge |
26,888 |
robocasa_CloseFridgeDrawer |
14,946 |
robocasa_CloseMicrowave |
20,075 |
robocasa_CloseOven |
18,230 |
robocasa_CloseStandMixerHead |
11,593 |
robocasa_CloseToasterOvenDoor |
19,815 |
robocasa_CoffeeServeMug |
16,921 |
robocasa_CoffeeSetupMug |
23,636 |
robocasa_LowerHeat |
31,174 |
robocasa_MakeIcedCoffee |
29,048 |
robocasa_NavigateKitchen |
79,550 |
robocasa_OpenBlenderLid |
20,124 |
robocasa_OpenCabinet |
37,492 |
robocasa_OpenDishwasher |
18,086 |
robocasa_OpenDrawer |
20,488 |
robocasa_OpenElectricKettleLid |
10,928 |
robocasa_OpenFridge |
33,138 |
robocasa_OpenFridgeDrawer |
18,517 |
robocasa_OpenMicrowave |
26,017 |
robocasa_OpenOven |
15,555 |
robocasa_OpenStandMixerHead |
13,411 |
robocasa_OpenToasterOvenDoor |
15,469 |
robocasa_PackDessert |
27,994 |
robocasa_PickPlaceCabinetToCounter |
20,201 |
robocasa_PickPlaceCounterToBlender |
38,892 |
robocasa_PickPlaceCounterToCabinet |
24,225 |
robocasa_PickPlaceCounterToDrawer |
28,225 |
robocasa_PickPlaceCounterToMicrowave |
42,012 |
robocasa_PickPlaceCounterToOven |
32,014 |
robocasa_PickPlaceCounterToSink |
22,410 |
robocasa_PickPlaceCounterToStandMixer |
25,467 |
robocasa_PickPlaceCounterToStove |
24,039 |
robocasa_PickPlaceCounterToToasterOven |
24,313 |
robocasa_PickPlaceDrawerToCounter |
31,819 |
robocasa_PickPlaceFridgeDrawerToShelf |
26,396 |
robocasa_PickPlaceFridgeShelfToDrawer |
27,047 |
robocasa_PickPlaceMicrowaveToCounter |
38,729 |
robocasa_PickPlaceSinkToCounter |
26,397 |
robocasa_PickPlaceStoveToCounter |
23,003 |
robocasa_PickPlaceToasterOvenToCounter |
19,323 |
robocasa_PickPlaceToasterToCounter |
26,907 |
robocasa_PreheatOven |
21,102 |
robocasa_SlideDishwasherRack |
19,052 |
robocasa_SlideOvenRack |
23,958 |
robocasa_SlideToasterOvenRack |
11,496 |
robocasa_StartCoffeeMachine |
13,722 |
robocasa_TurnOffMicrowave |
15,233 |
robocasa_TurnOffSinkFaucet |
12,309 |
robocasa_TurnOffStove |
32,741 |
robocasa_TurnOnBlender |
11,698 |
robocasa_TurnOnElectricKettle |
12,460 |
robocasa_TurnOnMicrowave |
14,010 |
robocasa_TurnOnSinkFaucet |
23,795 |
robocasa_TurnOnStove |
17,910 |
robocasa_TurnOnToaster |
10,042 |
robocasa_TurnOnToasterOven |
17,051 |
robocasa_TurnSinkSpout |
11,130 |
DexMimicGen — dexmimicgen/ (9 bimanual tasks, 2,915,177 frames)
DexMimicGen bimanual dexterous tasks (NVIDIA,
ICRA 2025) across three robot configs — bimanual Panda, Panda + dexterous hands
(PandaDexRH/LH), and the GR1 humanoid — replayed from recorded states. Native
cameras are agentview + two wrist views, so sideview is the injected world camera.
action is 14-dim (bimanual Panda) or 24-dim (dexterous / GR1); proprio obs keys
span robot0/robot1 (and GR1 left/right).
| dataset | frames |
|---|---|
dexmimicgen_two_arm_box_cleanup |
234,398 |
dexmimicgen_two_arm_can_sort_random |
322,073 |
dexmimicgen_two_arm_coffee |
326,707 |
dexmimicgen_two_arm_drawer_cleanup |
298,235 |
dexmimicgen_two_arm_lift_tray |
516,848 |
dexmimicgen_two_arm_pouring |
338,519 |
dexmimicgen_two_arm_threading |
218,858 |
dexmimicgen_two_arm_three_piece_assembly |
239,827 |
dexmimicgen_two_arm_transport |
419,712 |
Loading
from huggingface_hub import snapshot_download
import lance
local = snapshot_download(
"MinghaoFu/owam", repo_type="dataset",
allow_patterns="robomimic/robomimic_lift.lance/*", # or "libero/*"
)
ds = lance.dataset(f"{local}/robomimic/robomimic_lift.lance")
print(ds.schema.names) # note: pixels, sideview, robot0_eye_in_hand
print(ds.to_table(limit=2).to_pandas())
Provenance and licensing
The demonstrations were replayed and re-rendered to three 224×224 cameras. They come from:
- robomimic — Mandlekar et al., What Matters in Learning from Offline Human Demonstrations for Robot Manipulation, CoRL 2021.
- MimicGen — Mandlekar et al., MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations, CoRL 2023.
- LIBERO — Liu et al., LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning, NeurIPS 2023.
- RoboCasa — Nasiriany et al., RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots, RSS 2024 (v0.2 LeRobot release).
- DexMimicGen — Jiang et al., DexMimicGen: Automated Data Generation for Bimanual Dexterous Manipulation via Imitation Learning, ICRA 2025.
Upstream sources are MIT-licensed; this dataset redistributes derived renders for research use.