GR1 Robot Tabletop Simulation 3D Assets

NVIDIA's PhysicalAI DigitalCousin Assets provide a collection of 3D meshes, textures, and object metadata for simulated tabletop manipulation environments. These digital assets, including mugs, bottles, bowls, and containers, populate virtual scenes for the GR1 robot. The dataset was published by NVIDIA and last updated in June 2025.

Use Cases

• Training robotic manipulation policies using 3D mesh geometry and object metadata for physics simulation.
• Benchmarking robot performance on tabletop tasks with standardized assets like mugs and bottles.
• Developing computer vision models for object recognition and pose estimation from provided textures and 3D models.
• Creating synthetic datasets for sim-to-real transfer by rendering scenes with these asset collections.
• Studying grasp planning and object interaction using the physical properties inferred from the asset metadata.

Strengths

• Assets are designed for a specific, high-fidelity robotics simulation platform (GR1).
• Collection includes multiple asset types (mugs, bottles, bowls, containers) for diverse scene composition.

Limitations

• Unknown total number of assets, meshes, or textures limits assessment of scope.
• Lack of column or metadata schema details prevents understanding of specific object properties.
• Potential bias towards tabletop objects may limit use for other robotic manipulation domains.

Provenance

Source

NVIDIA

Collection Method

Digitally created assets for simulation.

Freshness

Updated June 2025.