datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
dual-lidar-umi-relativeThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"observation.state": {
"dtype": "float32",
"shape": [
12
],
"names": [
"umi1_x",
"umi1_y",
"umi1_z",
"umi1_rx",
"umi1_ry",
"umi1_rz",
"umi2_x"… See the full description on the dataset page: https://huggingface.co/datasets/brandonyang/dual-lidar-umi-relative.dual-lidar-umiThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"observation.state": {
"dtype": "float32",
"shape": [
12
],
"names": [
"umi1_x",
"umi1_y",
"umi1_z",
"umi1_rx",
"umi1_ry",
"umi1_rz",
"umi2_x"… See the full description on the dataset page: https://huggingface.co/datasets/brandonyang/dual-lidar-umi.dual-lidar-combined-filtered-long-gripper
Combined filtered dual-LiDAR UMI demonstrations
Observation-only LeRobot v3 derivative of brandonyang/dual-lidar-umi, brandonyang/dual-lidar-umi-relative. It contains 182 demonstrations (179951 frames) accepted by the continuous bimanual YAM replayability pipeline.
The 12-D observation.state contains the smoothed, trajectory-optimized YAM-achievable path in the zero-origin UMI Cartesian convention. Raw UMI gripper widths remain as separate observations. The two original UMI… See the full description on the dataset page: https://huggingface.co/datasets/brandonyang/dual-lidar-combined-filtered-long-gripper.robot-umi-lidar3d-e2eThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"observation.images.front": {
"dtype": "video",
"shape": [
1200,
1920,
3
],
"names": [
"height",
"width",
"channels"
],
"info": {… See the full description on the dataset page: https://huggingface.co/datasets/brandonyang/robot-umi-lidar3d-e2e.dual-lidar-combined-filtered
Combined filtered dual-LiDAR UMI demonstrations
Observation-only LeRobot v3 derivative of brandonyang/dual-lidar-umi, brandonyang/dual-lidar-umi-relative. It contains 157 demonstrations (156492 frames) accepted by the continuous bimanual YAM replayability pipeline.
The 12-D observation.state contains the smoothed, trajectory-optimized YAM-achievable path in the zero-origin UMI Cartesian convention. Raw UMI gripper widths remain as separate observations. The two original UMI… See the full description on the dataset page: https://huggingface.co/datasets/brandonyang/dual-lidar-combined-filtered.dual-lidar-combined-filtered-joint-positions
Combined filtered dual-LiDAR UMI demonstrations
Observation-only LeRobot v3 derivative of brandonyang/dual-lidar-umi, brandonyang/dual-lidar-umi-relative. It contains 157 demonstrations (156492 frames) accepted by the continuous bimanual YAM replayability pipeline.
The 14-D observation.state contains left YAM joints 0–5, normalized left gripper, right YAM joints 0–5, and normalized right gripper. The two original UMI videos, timestamps, frame cadence, and task are preserved;… See the full description on the dataset page: https://huggingface.co/datasets/brandonyang/dual-lidar-combined-filtered-joint-positions.dual-lidar-combined-filtered-joint-positions-long-gripper
Combined filtered dual-LiDAR UMI demonstrations
Observation-only LeRobot v3 derivative of brandonyang/dual-lidar-umi, brandonyang/dual-lidar-umi-relative. It contains 182 demonstrations (179951 frames) accepted by the continuous bimanual YAM replayability pipeline.
The 14-D observation.state contains left YAM joints 0–5, normalized left gripper, right YAM joints 0–5, and normalized right gripper. The two original UMI videos, timestamps, frame cadence, and task are preserved;… See the full description on the dataset page: https://huggingface.co/datasets/brandonyang/dual-lidar-combined-filtered-joint-positions-long-gripper.egostation-iphone-lidar-household-v1
Zen-O Household Manipulation, iPhone LiDAR
8 first-person recordings of ordinary household work, with both hands
tracked in three dimensions and in real metres, laid out in LeRobot v2.1.
Episodes
8
Frames
128,833 at 30 fps, about 71.6 minutes
Video
observation.images.head, 1920x1440
State
7 floats, camera position and orientation
Action
20 floats, both wrists and both grippers
Coordinate frame
ROS REP 103, X forward, Y left, Z up, metric… See the full description on the dataset page: https://huggingface.co/datasets/zeno-labs/egostation-iphone-lidar-household-v1.robot-umi-lidar-sdk-e2eThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"observation.images.front": {
"dtype": "video",
"shape": [
1200,
1920,
3
],
"names": [
"height",
"width",
"channels"
],
"info": {… See the full description on the dataset page: https://huggingface.co/datasets/brandonyang/robot-umi-lidar-sdk-e2e.dual-lidar-umi-relative-filtered
Filtered dual-LiDAR UMI demonstrations
Observation-only LeRobot v3 derivative of brandonyang/dual-lidar-umi-relative. It contains 65 demonstrations (63383 frames) that pass the complete continuous YAM replayability classification.
observation.state retains the original 12-D UMI Cartesian schema. Its values are the smoothed, trajectory-optimized YAM-achievable FK path mapped back into the UMI coordinate convention. Gripper observations, videos, timestamps, and tasks are preserved… See the full description on the dataset page: https://huggingface.co/datasets/brandonyang/dual-lidar-umi-relative-filtered.dual-lidar-umi-independentThis dataset was created using LeRobot.
Dataset Description
Standalone LeRobot v3 dataset containing 296 dual-UMI orange-collection demonstrations (276,332 frames, 2.559 hours at 30 FPS). It contains synchronized observation.images.umi1 and observation.images.umi2 video observations, 14D observation.state, and 14D action; no LiDAR files or LiDAR frame features are included.
For each UMI independently, pose is expressed relative to that UMI's episode-start pose using… See the full description on the dataset page: https://huggingface.co/datasets/brandonyang/dual-lidar-umi-independent.dual-lidar-umi-testThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"observation.state": {
"dtype": "float32",
"shape": [
12
],
"names": [
"umi1_x",
"umi1_y",
"umi1_z",
"umi1_rx",
"umi1_ry",
"umi1_rz",
"umi2_x"… See the full description on the dataset page: https://huggingface.co/datasets/brandonyang/dual-lidar-umi-test.tartanground_lidardouvras-lidar-risk-synthetic
Douvras LiDAR Risk Synthetic v0.1
Benchmark tabular sintético de risco em corredores LiDAR. Cada linha representa
estatísticas resumidas de uma cena (clearance, densidade de pontos, vegetação e fios) e
um rótulo low, attention, warning ou critical produzido por uma regra explícita.
As cenas são disjuntas entre train, validation e test (36/12/12 registros). Não há
imagens aéreas, nuvens de pontos de clientes ou dados TTPLA neste release. O benchmark
serve para validar o pipeline… See the full description on the dataset page: https://huggingface.co/datasets/dougdotcon/douvras-lidar-risk-synthetic.power_line_lidar_datadual-lidar-umi-relative-testThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"observation.state": {
"dtype": "float32",
"shape": [
12
],
"names": [
"umi1_x",
"umi1_y",
"umi1_z",
"umi1_rx",
"umi1_ry",
"umi1_rz",
"umi2_x"… See the full description on the dataset page: https://huggingface.co/datasets/brandonyang/dual-lidar-umi-relative-test.dual-lidar-umi-filtered
Filtered dual-LiDAR UMI demonstrations
Observation-only LeRobot v3 derivative of brandonyang/dual-lidar-umi. It contains 54 demonstrations (52067 frames) that pass the complete continuous YAM replayability classification.
observation.state retains the original 12-D UMI Cartesian schema. Its values are the smoothed, trajectory-optimized YAM-achievable FK path mapped back into the UMI coordinate convention. Gripper observations, videos, timestamps, and tasks are preserved on the… See the full description on the dataset page: https://huggingface.co/datasets/brandonyang/dual-lidar-umi-filtered.clean_lidar_20260523_191037This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos"
],
"shape": [
6… See the full description on the dataset page: https://huggingface.co/datasets/siddpr/clean_lidar_20260523_191037.clean_lidar_20260523_190118This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos"
],
"shape": [
6… See the full description on the dataset page: https://huggingface.co/datasets/siddpr/clean_lidar_20260523_190118.power_line_lidar_data_testlidar-nuscenes-reasoninglidar-reasoning-250k