# Robotics Simulation

Published articles for Robotics Simulation.

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## How to Use AI Agents to Prepare 3D Scenes for Simulation

DevFeed: [How to Use AI Agents to Prepare 3D Scenes for Simulation](<https://devfeed.tech/articles/how-to-use-ai-agents-to-prepare-3d-scenes-for-simulation-31484.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/how-to-use-ai-agents-to-prepare-3d-scenes-for-simulation/>)

Author: Tanya Lenz

Published: 2026-09-16T23:20:33Z

Content type: tutorial

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Simulation](<https://devfeed.tech/topics/simulation.md>), [Physical AI](<https://devfeed.tech/topics/physical-ai.md>), [Simulation and Design](<https://devfeed.tech/topics/simulation-and-design.md>), [blender](<https://devfeed.tech/topics/blender.md>), [Isaac Sim](<https://devfeed.tech/topics/isaac-sim.md>), [Omniverse](<https://devfeed.tech/topics/omniverse.md>), [Robotics Simulation](<https://devfeed.tech/topics/robotics-simulation.md>), [Robotics](<https://devfeed.tech/topics/robotics.md>)

Tags: [3d](<https://devfeed.tech/tags/3d.md>), [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [blender](<https://devfeed.tech/tags/blender.md>), [gpt-6-astra](<https://devfeed.tech/tags/gpt-6-astra.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [isaac-sim](<https://devfeed.tech/tags/isaac-sim.md>), [nemoclaw](<https://devfeed.tech/tags/nemoclaw.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [omniverse](<https://devfeed.tech/tags/omniverse.md>), [openai](<https://devfeed.tech/tags/openai.md>), [openusd](<https://devfeed.tech/tags/openusd.md>), [physical-ai](<https://devfeed.tech/tags/physical-ai.md>), [robotics](<https://devfeed.tech/tags/robotics.md>), [robotics-simulation](<https://devfeed.tech/tags/robotics-simulation.md>), [simulation](<https://devfeed.tech/tags/simulation.md>), [simulation-modeling-design](<https://devfeed.tech/tags/simulation-modeling-design.md>)

### AI overview

This tutorial describes an agentic workflow for preparing Blender 3D scenes for robotics simulation. It covers scene inspection, OpenUSD metadata, physics properties, rendering preflight views, and validation for simulation-ready handoff to NVIDIA Isaac Sim or Isaac Lab.

### Source excerpt

Agentic AI workflows can be used to prepare and validate digital twins for physical AI systems. Agents can inspect 3D scenes, author simulation-relevant data in...

## Post-Train NVIDIA Cosmos 3 Edge for On-Device Robot Control

DevFeed: [Post-Train NVIDIA Cosmos 3 Edge for On-Device Robot Control](<https://devfeed.tech/articles/post-train-nvidia-cosmos-3-edge-for-on-device-robot-control-6920.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/post-train-nvidia-cosmos-3-edge-for-on-device-robot-control/>)

Author: Michelle Horton

Published: 2026-08-19T16:00:00Z

Content type: tutorial

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [Cosmos](<https://devfeed.tech/topics/cosmos.md>), [AI, ML & Data Engineering](<https://devfeed.tech/topics/ai-ml-data-engineering.md>)

Tags: [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [cosmos](<https://devfeed.tech/tags/cosmos.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [edge](<https://devfeed.tech/tags/edge.md>), [edge-computing](<https://devfeed.tech/tags/edge-computing.md>), [featured](<https://devfeed.tech/tags/featured.md>), [foundation-models](<https://devfeed.tech/tags/foundation-models.md>), [inference](<https://devfeed.tech/tags/inference.md>), [jetson](<https://devfeed.tech/tags/jetson.md>), [latency](<https://devfeed.tech/tags/latency.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [on-device](<https://devfeed.tech/tags/on-device.md>), [physical-ai](<https://devfeed.tech/tags/physical-ai.md>), [post-training](<https://devfeed.tech/tags/post-training.md>), [robotics](<https://devfeed.tech/tags/robotics.md>), [robotics-simulation](<https://devfeed.tech/tags/robotics-simulation.md>), [robots](<https://devfeed.tech/tags/robots.md>), [simulation-modeling-design](<https://devfeed.tech/tags/simulation-modeling-design.md>), [thor](<https://devfeed.tech/tags/thor.md>), [tutorial](<https://devfeed.tech/tags/tutorial.md>)

### AI overview

A tutorial on post-training NVIDIA Cosmos 3 Edge as an on-device robot manipulation policy, serving it on Jetson Thor, running receding-horizon inference, and evaluating it in closed-loop simulation.

### Source excerpt

Robots need policies that can adapt to their sensors, environments, and tasks while running on onboard computing hardware. World models offer a foundation for...

## Develop Humanoid Robot Policies End-to-End with NVIDIA Isaac GR00T

DevFeed: [Develop Humanoid Robot Policies End-to-End with NVIDIA Isaac GR00T](<https://devfeed.tech/articles/develop-humanoid-robot-policies-end-to-end-with-nvidia-isaac-gr00t-6803.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/develop-humanoid-robot-policies-end-to-end-with-nvidia-isaac-gr00t/>)

Author: Elizabeth Goodman

Published: 2026-07-07T17:05:42Z

Content type: article

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [Robotics](<https://devfeed.tech/topics/robotics.md>), [Model Development](<https://devfeed.tech/topics/model-development.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Training AI Models](<https://devfeed.tech/topics/training-ai-models.md>), [datasets](<https://devfeed.tech/topics/datasets.md>), [multimodal](<https://devfeed.tech/topics/multimodal.md>), [Deployment](<https://devfeed.tech/topics/deployment.md>), [Simulation and Design](<https://devfeed.tech/topics/simulation-and-design.md>), [Tooling](<https://devfeed.tech/topics/tooling.md>)

Tags: [ai-foundation-models](<https://devfeed.tech/tags/ai-foundation-models.md>), [apache](<https://devfeed.tech/tags/apache.md>), [building](<https://devfeed.tech/tags/building.md>), [data](<https://devfeed.tech/tags/data.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [developers](<https://devfeed.tech/tags/developers.md>), [development](<https://devfeed.tech/tags/development.md>), [evaluation](<https://devfeed.tech/tags/evaluation.md>), [featured](<https://devfeed.tech/tags/featured.md>), [humanoid-robots](<https://devfeed.tech/tags/humanoid-robots.md>), [images](<https://devfeed.tech/tags/images.md>), [integrations](<https://devfeed.tech/tags/integrations.md>), [isaac](<https://devfeed.tech/tags/isaac.md>), [isaac-sim](<https://devfeed.tech/tags/isaac-sim.md>), [manufacturing](<https://devfeed.tech/tags/manufacturing.md>), [model](<https://devfeed.tech/tags/model.md>), [multimodal](<https://devfeed.tech/tags/multimodal.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [robotics](<https://devfeed.tech/tags/robotics.md>), [robotics-simulation](<https://devfeed.tech/tags/robotics-simulation.md>), [robots](<https://devfeed.tech/tags/robots.md>), [simulation-modeling-design](<https://devfeed.tech/tags/simulation-modeling-design.md>), [software](<https://devfeed.tech/tags/software.md>), [tooling](<https://devfeed.tech/tags/tooling.md>), [training](<https://devfeed.tech/tags/training.md>), [workflows](<https://devfeed.tech/tags/workflows.md>)

### AI overview

NVIDIA Isaac GR00T Development Platform unifies humanoid robot development workflows, combining data collection, simulation-based training, evaluation, and deployment. The article highlights the open Isaac GR00T 1.7 vision-language-action model, which accepts language and images and can be adapted to robots, tasks, and environments through post-training.

### Source excerpt

As more teams move from humanoid robot bring-up to task-specific skill development, the need for repeatable development workflows is growing. Building humanoids...