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Dataset

FreeTacMan

by OpenDriveLab hf-dataset--opendrivelab--freetacman
Nexus Index
38.5 Top 100%
S / A / P / R / Q Breakdown Calibration Pending

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Vital Performance
0 DL / 30D
0.0%
Data Integrity 38.5 FNI Score
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Dataset Information Summary
Entity Passport
Registry ID hf-dataset--opendrivelab--freetacman
License MIT
Provider huggingface
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Cite this dataset

Academic & Research Attribution

BibTeX
@misc{hf_dataset__opendrivelab__freetacman,
  author = {OpenDriveLab},
  title = {FreeTacMan Dataset},
  year = {2026},
  howpublished = {\url{https://huggingface.co/datasets/opendrivelab/freetacman}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
OpenDriveLab. (2026). FreeTacMan [Dataset]. Free2AITools. https://huggingface.co/datasets/opendrivelab/freetacman

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Full Specifications [+]

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Authority (A) 0
Popularity (P) 0
Recency (R) 0
Quality (Q) 0

๐Ÿ’ฌ Index Insight

FNI V2.0 for FreeTacMan: Semantic (S:0), Authority (A:0), Popularity (P:0), Recency (R:0), Quality (Q:0).

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Dataset Specification

๐Ÿ“ฆ FreeTacman

Robot-free Visuo-Tactile Data Collection System for Contact-rich Manipulation [ICRA 2026]

๐ŸŽฏ Overview

This dataset supports the paper FreeTacman: Robot-free Visuo-Tactile Data Collection System for Contact-rich Manipulation. It contains a large-scale, high-precision visuo-tactile manipulation dataset with over 3000k visuo-tactile image pairs, more than 10k trajectories across 50 tasks. We provide ๐Ÿค— Script (Hugging Face) and ๐Ÿ‘พ Script (ModelScope) (users in China) for downloading the dataset.

FreeTacMan System Overview Please refer to our ๐Ÿš€ Website | ๐Ÿ“„ Paper | ๐Ÿ’ป Code | ๐Ÿ› ๏ธ Hardware Guide | ๐Ÿ“บ Video | ๐ŸŒ X for more details.

๐Ÿ”ฌ Potential Applications

The FreeTacman dataset enables diverse research directions in visuo-tactile learning and manipulation:

  • System Reproduction: For researchers interested in hardware implementation, you can reproduce FreeTacMan from scratch using our ๐Ÿ› ๏ธ Hardware Guide and ๐Ÿ’ป Code.

  • Multimodal Imitation Learning: Transfer to other LED-based tactile sensors (such as GelSight) for developing robust multimodal imitation learning frameworks.

  • Tactile-aware Grasping: Utilize the dataset for pre-training tactile representation models and developing tactile-aware reasoning systems.

  • Simulation-to-Real Transfer: Leverage the dynamic tactile interaction sequences to enhance tactile simulation fidelity, significantly reducing the sim2real gap.

๐Ÿ“‚ Dataset Structure

The dataset is organized into 50 task categories, each containing:

  • Video files: Synchronized video recordings from the wrist-mounted and visuo-tactile cameras for each demonstration
  • Trajectory files: Detailed tracking data for tool center point pose and gripper distance

๐Ÿงพ Data Format

Video Files

  • Format: MP4
  • Views: Wrist-mounted camera and visuo-tactile camera perspectives per demonstration

Trajectory Files

Each trajectory file contains the following data columns:

Timestamp

  • timestamp - Unix Timestamp

Tool Center Point (TCP) Data

  • TCP_pos_x, TCP_pos_y, TCP_pos_z - TCP position
  • TCP_euler_x, TCP_euler_y, TCP_euler_z - TCP orientation (euler angles)
  • quat_w, quat_x, quat_y, quat_z - TCP orientation (quaternion representation)

Gripper Data

  • gripper_distance - Gripper opening distance

๐Ÿ“ Citation

If you use this dataset in your research, please cite:

bibtex
@article{wu2025freetacman,
  title={FreeTacMan: Robot-free visuo-tactile data collection system for contact-rich manipulation},
  author={Wu, Longyan and Yu, Checheng and Ren, Jieji and Chen, Li and Jiang, Yufei and Huang, Ran and Gu, Guoying and Li, Hongyang},
  journal={IEEE International Conference on Robotics and Automation},
  year={2026}
}

๐Ÿ’ผ License

This dataset is released under the MIT License. See LICENSE file for details.

๐Ÿ“ง Contact

For questions or issues regarding the dataset, please contact: Longyan Wu ([email protected]).

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๐Ÿ†” Identity & Source

id
hf-dataset--opendrivelab--freetacman
slug
opendrivelab--freetacman
source
huggingface
author
OpenDriveLab
license
MIT
tags
task_categories:robotics, license:mit, modality:video, arxiv:2506.01941, region:us, tactile

โš™๏ธ Technical Specs

architecture
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params billions
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context length
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pipeline tag

๐Ÿ“Š Engagement & Metrics

downloads
33,124
stars
4
forks
0

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