Data Product Features

Distribution

Format

• MP4 video files
• Hand pose and tactile contact data files (e.g., CSV, JSON, or equivalent)

Encoding

• H.264 / H.265

Structure

• Folder-based organization containing synchronized videos and tactile glove sensor data.

Data Volume

• Approximate Duration: 50 hours
• Approximate Storage Size: 350 GB
• Approximate Records: 5,000 synchronized recordings

Usage

• Dexterous Manipulation: Training robots for complex object handling.
• Grasp Planning: Learning stable grasp strategies using tactile feedback.
• Imitation Learning: Teaching robots from human demonstrations.
• Hand Pose Estimation: Developing and evaluating hand tracking models.
• Tactile Perception: Studying contact-based sensing and interaction.
• Human–Robot Interaction: Improving robotic understanding of hand movements.
• Embodied AI: Training multimodal perception and manipulation systems.
• Academic Research: Robotics, tactile sensing, and computer vision research.

Coverage

Geographic Coverage

Time Range

• Start Date: Not specified
• End Date: Not specified

Demographics

• Adults (where applicable)
• Mixed gender participants
• Industrial workplaces (60%)
• Household environments (40%)

License

AI Training Rights

• Use the Data Product to train, fine-tune, and evaluate machine learning models, including large language models.
• Incorporate Data Product content into models and commercialize resulting model outputs.
• Create derivative works (model weights, embeddings, feature representations, etc.) for any lawful purpose.

Restrictions

• The Data Product itself may not be sold, redistributed, or shared as a standalone dataset outside of licensed usage.
• Licensee must comply with all applicable privacy, data protection, and intellectual property laws.

Who Can Use It

• Data Scientists: Train multimodal AI and robotics models using vision and tactile data.
• Researchers: Conduct research in tactile sensing, dexterous manipulation, and human hand motion.
• Robotics Engineers: Develop robotic grasping, manipulation, and perception systems.
• Businesses: Build AI-powered robotic manipulation and automation solutions.
• Universities: Support robotics, AI, and human–computer interaction research and education.

Data Dictionary

Additional Notes

• Collected across industrial (60%) and household (40%) environments in Asia.
• Combines synchronized visual recordings with tactile glove data, including hand pose and contact information.
• Recorded using a GoPro or equivalent camera in 4K and 1080p at 30/60 FPS with H.264/H.265 encoding.
• Audio is included.
• Suitable for robotics, dexterous manipulation, tactile perception, grasp learning, imitation learning, embodied AI, and multimodal machine learning.
• Released under the CC0 license for both research and commercial AI applications.

Asia Tactile Glove Dataset (Hand Pose + Contact Data)

Description

Data Product Features

Distribution

Format

• MP4 video files
• Hand pose and tactile contact data files (e.g., CSV, JSON, or equivalent)

Encoding

• H.264 / H.265

Structure

• Folder-based organization containing synchronized videos and tactile glove sensor data.

Data Volume

• Approximate Duration: 50 hours
• Approximate Storage Size: 350 GB
• Approximate Records: 5,000 synchronized recordings

Usage

• Dexterous Manipulation: Training robots for complex object handling.
• Grasp Planning: Learning stable grasp strategies using tactile feedback.
• Imitation Learning: Teaching robots from human demonstrations.
• Hand Pose Estimation: Developing and evaluating hand tracking models.
• Tactile Perception: Studying contact-based sensing and interaction.
• Human–Robot Interaction: Improving robotic understanding of hand movements.
• Embodied AI: Training multimodal perception and manipulation systems.
• Academic Research: Robotics, tactile sensing, and computer vision research.

Coverage

Geographic Coverage

Time Range

• Start Date: Not specified
• End Date: Not specified

Demographics

• Adults (where applicable)
• Mixed gender participants
• Industrial workplaces (60%)
• Household environments (40%)

License

AI Training Rights

• Use the Data Product to train, fine-tune, and evaluate machine learning models, including large language models.
• Incorporate Data Product content into models and commercialize resulting model outputs.
• Create derivative works (model weights, embeddings, feature representations, etc.) for any lawful purpose.

Restrictions

• The Data Product itself may not be sold, redistributed, or shared as a standalone dataset outside of licensed usage.
• Licensee must comply with all applicable privacy, data protection, and intellectual property laws.

Who Can Use It

• Data Scientists: Train multimodal AI and robotics models using vision and tactile data.
• Researchers: Conduct research in tactile sensing, dexterous manipulation, and human hand motion.
• Robotics Engineers: Develop robotic grasping, manipulation, and perception systems.
• Businesses: Build AI-powered robotic manipulation and automation solutions.
• Universities: Support robotics, AI, and human–computer interaction research and education.

Data Dictionary

Additional Notes

• Collected across industrial (60%) and household (40%) environments in Asia.
• Combines synchronized visual recordings with tactile glove data, including hand pose and contact information.
• Recorded using a GoPro or equivalent camera in 4K and 1080p at 30/60 FPS with H.264/H.265 encoding.
• Audio is included.
• Suitable for robotics, dexterous manipulation, tactile perception, grasp learning, imitation learning, embodied AI, and multimodal machine learning.
• Released under the CC0 license for both research and commercial AI applications.