📦 FreeTacman

Robot-free Visuo-Tactile Data Collection System for Contact-rich Manipulation

🎯 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. Please refer to our 🚀 Website | 📄 Paper | 💻 Code | 🛠️ Hardware Guide | 📺 Video | 🌐 X for more details.

🔬 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 🛠️ Hardware Guide and 💻 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.

📂 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

🧾 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

📝 Citation

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

@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={arXiv preprint arXiv:2506.01941},
  year={2025}
}

💼 License

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

📧 Contact

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