newton-physics / newton

2025-04-22 · Source: Github Trending: All languages · Field: Technology & Digital — Robotics & Autonomous Systems, Artificial Intelligence & Machine Learning · Depth: Intermediate, short

Summary

Newton is a GPU-accelerated physics simulation engine designed for roboticists and simulation researchers. Built on NVIDIA Warp and integrating MuJoCo Warp as its primary backend, Newton extends Warp's deprecated `warp.sim` module. The engine emphasizes GPU-based computation, OpenUSD support, differentiability, and user-defined extensibility to facilitate rapid iteration and scalable robotics simulation. Newton is a Linux Foundation project, community-built and maintained, with code licensed under Apache-2.0 and documentation under CC-BY-4.0. It was initiated by Disney Research, Google DeepMind, and NVIDIA, and requires Python 3.10+, Linux/Windows/macOS (macOS is CPU-only), and an NVIDIA GPU (Maxwell or newer) with driver 545+ for GPU acceleration.

Key takeaway

For AI Scientists developing advanced robotics or simulation models, Newton offers a robust, GPU-accelerated, and differentiable physics engine. You should consider integrating Newton to accelerate simulation workflows, especially when requiring high-fidelity physics, OpenUSD compatibility, or gradient-based optimization for control and learning tasks. Explore its diverse examples to understand its capabilities for your specific research needs.

Key insights

Newton offers a GPU-accelerated, differentiable physics engine for scalable robotics simulation.

Principles

• Prioritize GPU-based computation
• Ensure differentiability for optimization
• Support OpenUSD for interoperability

Method

Install Newton via `pip install "newton[examples]"` and run examples using `python -m newton.examples [example_name]` with optional viewer, device, and frame arguments.

In practice

• Simulate various robot types (e.g., Anymal, UR10)
• Model complex materials like cables and cloth
• Perform inverse kinematics and multi-physics simulations

Topics

• GPU Physics Simulation
• Robotics Simulation
• NVIDIA Warp
• Differentiable Simulation
• OpenUSD

Code references

• newton-physics/newton
• NVIDIA/warp
• google-deepmind/mujoco_warp
• newton-physics/newton-governance

Best for: AI Scientist, Robotics Engineer, Research Scientist, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Github Trending: All languages.