From Simulation to Production: How to Build Robots With AI

2026-03-18 · Source: NVIDIA Blog · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems · Depth: Intermediate, quick

Summary

ABB Robotics and NVIDIA have partnered to integrate industrial-grade physical AI into factory operations by embedding NVIDIA Omniverse libraries directly into ABB's RobotStudio programming and simulation software. This collaboration enables customers to design, simulate, and optimize entire production cells or complex robot fleets in a virtual environment before physical deployment. The solution leverages NVIDIA's AI capabilities for perception, manipulation, and human-robot interaction, allowing robots to learn and adapt to variations in real-world manufacturing. This advancement aims to enhance flexibility, efficiency, and resilience in industrial automation, addressing challenges like labor shortages and the need for rapid production changes.

Key takeaway

For manufacturing executives evaluating automation upgrades, this partnership signifies a critical shift towards more adaptable and efficient factory floors. You should explore integrating digital twin simulation with AI-driven robotics to accelerate deployment, reduce risks, and enhance operational flexibility, especially when facing labor constraints or dynamic production demands.

Key insights

Integrating physical AI with digital twins enhances industrial automation design and deployment.

Principles

• Simulate before physical deployment.
• AI improves robot perception and adaptation.

Method

Embed NVIDIA Omniverse libraries into robot programming software to design, simulate, and optimize production cells virtually before physical deployment.

In practice

• Design complex robot fleets virtually.
• Optimize production cells in simulation.

Topics

• ABB Robotics
• NVIDIA Omniverse
• Industrial AI
• Physical AI
• RobotStudio

Best for: CTO, VP of Engineering/Data, Director of AI/ML, Robotics Engineer, AI Engineer, Automation Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by NVIDIA Blog.