Simulated Tabletop Objects for GR1 Robot Manipulation

PhysicalAI DigitalCousin Assets from NVIDIA provide a collection of 3D meshes, textures, and object metadata for simulated tabletop manipulation environments. These assets, including items like mugs, bottles, bowls, and containers, populate virtual scenes for robotic interaction and benchmarking. The dataset was last updated by NVIDIA in June 2025.

Use Cases

• Training robotic grasping policies using the 3D mesh geometry and physical properties of objects like mugs and bottles.
• Benchmarking object recognition and pose estimation algorithms against the provided textures and object metadata.
• Simulating complex tabletop manipulation tasks, such as stacking containers or pouring from bottles, using the interactive scene assets.
• Developing and testing robotic control systems for the GR1 robot within a physics-accurate virtual environment populated by these assets.

Strengths

• Assets are specifically designed for the GR1 humanoid robot, ensuring relevance for targeted robotics research.
• Includes multiple asset types (3D meshes, textures, metadata) for comprehensive scene construction.

Limitations

• The exact number of unique assets (rows), file sizes, and specific object categories are not provided.
• Asset quality and physical realism are unverified without sample data or detailed specifications.
• License terms are unknown, which could restrict commercial or redistribution use.

Provenance

Source

NVIDIA

Collection Method

Created as digital assets for simulation purposes.

Freshness

Last updated June 2025.