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HapTile → FiftyOne (Native Multimodal MCAP)
HapTile, a haptic-informed vision-tactile-language-action dataset, converted to native multimodal MCAP episodes.
A UR5e arm with a Robotiq 2F-85 gripper works through contact-rich tabletop tasks under teleoperation. Each gripper finger carries a vision-based tactile sensor that films a gel pad printed with a marker grid, so the contact shows as the markers moving. Two RGB-D cameras watch the scene, one facing the table and one on the wrist, and the haptic feedback the operator felt through the teleoperation rig is recorded alongside the robot state.
1,699 episodes across 38 tasks, 664,045 frames, 12.36 hours. In 1,592 of them the operator felt haptic feedback at some point, at the levels firm, mild, soft.
Installation
pip install fiftyone
Usage
import fiftyone as fo
import fiftyone.utils.huggingface as fouh
dataset = fouh.load_from_hub(
"Voxel51/HapTile",
name="HapTile",
persistent=True,
)
fo.launch_app(dataset)
The episodes with the firmest contact on the right fingertip:
view = dataset.sort_by("peak_marker_motion_right", reverse=True)
fo.launch_app(dataset, view=view)
What you get
Each episode contains:
/front-cameraand/wrist-camera, the two RGB views, asfoxglove.CompressedVideo/tactile-leftand/tactile-right, the two fingertip gel pads, asfoxglove.CompressedVideo/front-depthand/wrist-depth, the depth renderings at 640x480, asfoxglove.CompressedVideo/tactile.plot, the marker motion each fingertip measures, with the release's summary of the two alongside/haptic-feedback, the feedback level the operator felt, written at each change/end-effector-posein the UR5e base frame, asfoxglove.PoseInFrame, with/end-effector.plotcarryingx,y,zand the rotation vector, and/end-effector-velocity.plotits linear and angular speed/joints.plotand/joint-velocities.plot, the six arm joints/command.plot, the commanded joint targets and gripper/gripper.plot, the gripper position/instruction, the task text
The colour and tactile streams are 320x240 except in move_mobile_box, whose 47 episodes record them at 640x480.
| Task | Episodes | Frames | Minutes | Instruction |
|---|---|---|---|---|
insert_peg |
50 | 40,656 | 45.2 | insert the peg in the red hole |
move_mobile_box |
61 | 29,702 | 29.2 | move the mobile box to the right side of the workspace |
move_disposable_cup |
60 | 26,898 | 32.4 | move the disposable cup to the bottom right side of the workspace |
put_apple |
63 | 24,319 | 27.1 | move the apple onto the red plate |
turn_cleanser_bottle |
30 | 23,114 | 25.7 | pour liquid from the cleanser bottle into the yellow bowl |
wipe_whiteboard |
50 | 22,860 | 25.5 | use the sponge to wipe the whiteboard and remove the marker drawing |
put_spray_bottle |
50 | 22,674 | 25.2 | put the transparent spray bottle on top of the drawer |
move_plush_toy |
70 | 22,636 | 27.0 | move the plush toy to the bottom left side of the workspace |
move_cable |
55 | 22,063 | 26.5 | move the cable to the bottom left side of the workspace |
remove_laundry_pod |
60 | 21,006 | 23.4 | remove a laundry pod from the box and place it on the green Tshirt in the laundry basket |
stack_glass_cups |
30 | 20,638 | 23.0 | add the glass cup on the table to the stack of glass cups on the left side of the dish rack |
move_water_bottle |
49 | 20,165 | 22.5 | move the water bottle to the bottom right side of the workspace |
put_orange |
47 | 19,647 | 21.9 | put the orange in the purple bowl |
turn_can |
30 | 19,466 | 21.7 | turn the can upright and place it onto the white tray |
put_baseball |
29 | 17,698 | 19.7 | put the baseball in the purple bowl |
fold_tshirt |
30 | 17,641 | 19.6 | fold the Tshirt from its bottom |
stack_disposable_cup |
51 | 17,118 | 19.1 | pick up the top cup from the stack of disposable cups and place it on the table |
remove_sugar_bag |
61 | 17,064 | 19.0 | remove one sugar bag and place it on the table |
turn_water_bottle |
39 | 16,842 | 18.8 | turn the water bottle upright and place it onto the white tray |
put_sponge |
31 | 16,825 | 18.7 | put the sponge in the red plate |
move_rubiks_cube |
30 | 15,202 | 16.9 | move the rubik's cube to the bottom right side of the workspace |
remove_cloth |
30 | 15,018 | 16.7 | remove the green Tshirt from the laundry basket and place it on the table |
move_can |
30 | 14,732 | 16.4 | move the can to the top right side of the workspace |
put_spoon |
49 | 14,391 | 16.0 | put the spoon in the glass cup |
put_spatula |
49 | 14,360 | 16.0 | put the spatula on top of the pan |
put_stack_glass_cups |
27 | 14,161 | 15.8 | put the stack of glass cups onto the red plate |
put_banana |
42 | 13,831 | 15.4 | put the banana onto the red plate |
put_fork |
50 | 13,823 | 15.4 | put the fork in the right side of the plate |
remove_screwdriver |
50 | 13,601 | 15.1 | remove the red screwdriver from the table and place it on the left side of the workspace |
press_coffee_machine |
50 | 13,562 | 15.1 | turn on the coffee machine by pressing the button |
remove_tissue |
47 | 12,839 | 14.3 | remove a paper tissue from the box and place it on the table |
move_spoon |
49 | 12,309 | 13.7 | move the spoon to the left side of the plate |
put_lego |
60 | 11,525 | 12.8 | put the black lego piece on the box |
stack_bowls |
50 | 11,486 | 12.8 | add the green bowl to the top of the bowl stack |
put_golf_ball |
50 | 9,350 | 10.4 | put the golf ball into the blue bowl |
remove_sticky_note |
30 | 9,057 | 10.1 | remove the green sticky note and place it on the table |
put_strawberry |
30 | 7,960 | 8.9 | put the strawberry onto the red plate |
move_toy_car |
30 | 7,806 | 8.7 | move the toy car into the transparent box |
Episodes carry the fields task, session, episode_index, recorded, instruction, num_frames, duration, fps, end_effector_path_m, gripper_min, gripper_max, peak_marker_motion_left, peak_marker_motion_right, haptic_feedback and haptic_feedback_frames.
Notes on the conversion
The source ships one zip per task holding a folder per episode, each with a trajectory.h5 that embeds the six camera streams as MPEG-4 Part 2 videos. Every stream is re-encoded to Annex-B H.264 without B-frames, one access unit per frame, frame for frame against the source's own count.
The source stamps every frame with the wall-clock time it was recorded, without a time zone. Episodes are placed on that clock relative to their first frame, so the frame rate varies as the recording did, and the start time is kept in recorded.
The depth streams arrive as 8-bit renderings rather than metric depth and are carried as video like the colour streams.
The release records the haptic channel in three ways. Most episodes carry the feedback level with the summed marker motion of both fingertips and its normalized form, which /tactile.plot carries as sum and normalized. Some carry the larger of the two fingertips instead, carried as max and normalized. The 47 episodes of move_mobile_box carry no haptic channel at all, so they have no /haptic-feedback stream and their haptic_feedback fields are empty.
Where the source's streams disagree in length, the difference is trailing: a final row with an empty timestamp, or a state array or video one frame longer than the rest. Every stream is cut to the shortest, which drops the longer streams' extra trailing frame in 40 episodes. One folder with an empty trajectory is left out.
The source's activated flag is set on every frame of every episode and its 30-channel touch array is zero throughout, so neither is carried.
The pose is published as a position and a rotation vector and is carried as one on /end-effector.plot, alongside the quaternion /end-effector-pose needs. The gripper entry of the source's joint array duplicates gripper_position and is carried once, on /gripper.plot.
Task names are lower-cased. The handful of still frames some episode folders carry beside the trajectory are not reproduced, and neither are the source's per-episode frame-rate reports, whose content the timestamps already hold.
License & attribution
The source release is distributed under CC BY 4.0, and this conversion is distributed under the same license.
@article{alian2026haptile,
title = {HapTile: A Haptic-Informed Vision-Tactile-Language-Action
Dataset for Contact-Rich Imitation Learning},
author = {Alian, Amirhosein and Zhao, Yongqiang and Gu, Shiyi and
Zhang, Xuyang and Chen, Zhuo and Mower, Christopher E. and
Bou-Ammar, Haitham and Luo, Shan},
journal = {arXiv preprint arXiv:2606.04825},
year = {2026}
}
Changes from the source: conversion to the FiftyOne MCAP flavor, re-encoding of the six camera streams from MPEG-4 Part 2 to H.264, the recording clock rebased to each episode's first frame, every stream cut to the shortest where the source's lengths disagree, the pose carried as a quaternion beside the source's rotation vector, task names lower-cased, the empty trajectory and the constant activated and touch arrays left out, and the robot state, tactile, haptic and instruction streams encoded as message streams.
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