TaF-Dataset

TaF-Dataset is a large-scale, synchronized tactile-force dataset introduced in TaF-VLA: Tactile-Force Alignment in Vision-Language-Action Models for Force-aware Manipulation. It is designed for learning force-aware tactile representations and studying contact-rich robotic manipulation.

During data collection, an ATI six-axis force/torque sensor records the interaction wrench (Fx, Fy, Fz, Tx, Ty, and Tz). A piezoelectric sensing array provides a spatial pressure map that identifies the contact region, while a vision-based tactile sensor records the corresponding tactile image. These signals are temporally synchronized, enabling models to associate local tactile deformation and contact location with the physical interaction force.

Dataset overview

• 10,053,265 synchronized frames
• 3,592 episodes
• 408 object/sensor sequences
• Tactile images, 12 x 12 pressure maps, and six-axis force/torque signals

The dataset covers six tactile-sensor configurations:

Configuration	Parent directory	Sequences
GelSight Mini with markers	taf_dataset/gs_mini/	124
GelSight Mini without markers	taf_dataset/gs_mini/	84
Custom-designed sensor without markers	taf_dataset/custom_designed/	84
Custom-designed sensor with 6 x 6 markers	taf_dataset/custom_designed/	74
Custom-designed sensor with 7 x 7 markers	taf_dataset/custom_designed/	10
Custom-designed sensor with 8 x 8 markers	taf_dataset/custom_designed/	32

Data modalities

Each frame contains the following synchronized observations:

Field	Shape	Description
observation.image	240 x 320 x 3	RGB tactile image
observation.pressure_matrix	12 x 12	Piezoelectric pressure map indicating the contact region and spatial pressure distribution
observation.force_torque	6	ATI force/torque measurement ordered as Fx, Fy, Fz, Tx, Ty, Tz
timestamp	1	Frame timestamp in seconds
frame_index	1	Frame index within the episode
episode_index	1	Episode identifier

The normal-force channel Fz provides the clearest indication of loading along the primary contact direction. The complete six-dimensional wrench is retained to capture tangential forces and rotational interaction dynamics.

Data organization

The dataset follows the LeRobot v3 layout. The repository is organized as follows:

TaF-Dataset/
├── README.md
└── taf_dataset/
    ├── gs_mini/
    │   ├── gs_mini_obj1/
    │   ├── ...
    │   └── gs_mini_wo_marker_obj84/
    └── custom_designed/
        ├── custom_designed_no_mark_obj1/
        ├── custom_designed_6*6_mark_obj1/
        ├── custom_designed_7*7_mark_obj1/
        ├── custom_designed_8*8_mark_obj1/
        └── ...

The gs_mini/ and custom_designed/ directories contain 208 and 200 recorded sequences, respectively. Every sequence uses the same LeRobot layout:

<sensor_configuration>_obj<ID>/
├── data/chunk-000/file-000.parquet
├── videos/observation.image/chunk-000/file-000.mp4
└── meta/
    ├── episodes/chunk-000/file-000.parquet
    ├── collection_config.json
    ├── info.json
    ├── stats.json
    └── tasks.parquet

All sequence-directory names use a numeric ID within their corresponding tactile-sensor configuration:

Relative path pattern	ID range
taf_dataset/gs_mini/gs_mini_obj<ID>	1–124
taf_dataset/gs_mini/gs_mini_wo_marker_obj<ID>	1–84
taf_dataset/custom_designed/custom_designed_no_mark_obj<ID>	1–84
taf_dataset/custom_designed/custom_designed_6*6_mark_obj<ID>	1–74
taf_dataset/custom_designed/custom_designed_7*7_mark_obj<ID>	1–10
taf_dataset/custom_designed/custom_designed_8*8_mark_obj<ID>	1–32

The numeric IDs are local to each sensor configuration: directories with the same ID but different prefixes represent separate recorded sequences and should not be assumed to contain the same physical object.

Citation

If this dataset is useful for your research, please cite:

@article{huang2026tafvla,
  title   = {TaF-VLA: Tactile-Force Alignment in Vision-Language-Action Models for Force-aware Manipulation},
  author  = {Huang, Yuzhe and Lin, Pei and Li, Wanlin and Li, Daohan and Li, Jiajun and Jiang, Jiaming and Xiao, Chenxi and Jiao, Ziyuan},
  journal = {arXiv preprint arXiv:2601.20321},
  year    = {2026}
}