Generate USD scene files from natural language descriptions for robot manipulation benchmarks.
npx skills add https://github.com/NVlabs/RoboLab --skill robolab-scenegen
Please help me install this Agent Skill. Skill: robolab-scenegen Source: https://github.com/NVlabs/RoboLab/tree/main/skills/robolab-scenegen Command: npx skills add https://github.com/NVlabs/RoboLab --skill robolab-scenegen
This skill removes the manual effort of building complex 3D simulation environments by translating natural language descriptions into valid USD scene files for robot manipulation tasks.
Invoke the robolab-scenegen skill and provide a description of the objects you want on the table to begin the automated scene generation process.
High-intent search queries and answers about installing and using this skill.
You can generate USD scene files by parsing natural language descriptions into spatial and physical constraints. This process automates object placement, collision-free configuration, and physics-based scene settling within the RoboLab ecosystem.
Yes, automated scene generation integrates with IsaacSim to perform physics-based settling. This ensures objects in the generated USD scenes are in stable, realistic resting positions for simulation validation.
Yes, you can create cluttered tabletop scenes by providing a text description of the desired objects. The skill automatically selects objects, computes collision-free placements, and generates the corresponding USDA file.
Yes, you need access to an object catalog to automate object placement. A compatible IsaacSim environment is also required to render and validate the physics-based scene settling.
Automating collision-free configuration is best handled by parsing text descriptions into spatial constraints. This computes valid object placements automatically, removing the manual effort of building complex 3D simulation environments.
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