NVIDIA launches Newton 1.0 physics engine for industrial robot training

2026-03-17 · Source: Dataconomy · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems · Depth: Advanced, quick

Summary

NVIDIA has released Newton 1.0, a production-ready open-source physics simulation engine designed for training robots in contact-rich manipulation and locomotion tasks, built on NVIDIA Warp and OpenUSD and co-developed with Google DeepMind and Disney Research. This stable platform, transitioning from its September 2025 beta, offers rigid-body solvers like MuJoCo Warp, which achieves up to 475 times faster performance for manipulation tasks on the NVIDIA RTX PRO 6000 Blackwell GPU compared to MJX. Newton 1.0 also features a Vertex Block Descent solver for deformable materials and integrates natively with Isaac Lab 3.0, with industry adoption by Toyota Research Institute, Skild AI for GPU rack assembly, and Samsung for refrigerator cable manipulation. Additionally, NVIDIA announced other robotics advancements at GTC, including Cosmos 3 and GR00T N2, which significantly improves robot task success rates. The company's Isaac and Omniverse frameworks now support an installed base exceeding 2 million robots globally, underscoring their widespread impact.

Key takeaway

NVIDIA Newton 1.0, a production-ready open-source physics simulation engine built on Warp and OpenUSD, significantly accelerates robot training for contact-rich manipulation and locomotion tasks. It achieves up to 475x speedup over MJX for manipulation on Blackwell GPUs, incorporating deformable simulation and hydroelastic contact modeling. This enables rapid, high-fidelity reinforcement learning for industrial automation, with early adoption by Skild AI and Samsung for complex assembly.

Topics

• NVIDIA Newton 1.0
• Physics Simulation
• Robot Training
• Industrial Automation
• Deformable Simulation

Best for: Machine Learning Engineer, AI Engineer, Robotics Engineer, MLOps Engineer

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