跳到正文
cccskills
免费在 GitHub 公开

using-ovnewton

Connect the Newton physics engine to an Omniverse simulation or ovstage with ovnewton. Use when importing a populated ovstage into Newton, stepping its physics, synchronizing stage edits, or publishing simulation state for Omniverse rendering.

中文简介正在准备中。当前显示原文说明。

查看安装方法

包含的文件(7)

  • SKILL.md5.2 KB
  • BENCHMARK.md8.2 KB
  • evals/config.yml198 B
  • evals/EVAL.md1.8 KB
  • evals/evals.json4.9 KB
  • skill-card.md5.3 KB
  • skill.oms.sig4.9 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Using ovnewton

Use ovnewton for the Newton ↔ ovstage bridge. The application owns model finalization, the solver, controls, collision handling, and the simulation loop. ovnewton reads a populated ovstage; Newton does not parse USD in this workflow. Standalone Newton simulations and generic Omniverse authoring do not need this skill.

Start from the supported examples

Install ovnewton in the application's environment. Let its package metadata select compatible dependencies; do not replace the qualified ovstage dependency with an arbitrary build.

pip install ovnewton
python -m ovnewton.examples.example_ovnewton_basic --device cpu --no-render --num-frames 8

For rendering or MuJoCo-Warp, install "ovnewton[examples]". The basic example accepts --solver mujoco or --solver vbd; VBD also supports CPU simulation. Rendering needs a supported NVIDIA GPU and its own device selection.

Read the getting-started guide and adapt the basic example. For multiple robots, use the robot example. Use documentation and examples corresponding to the installed ovnewton release; repository main may describe a newer API.

Construct and bind the simulation

  1. Call ovnewton.register_usd_schemas() before the first USD schema read. Create an ovstage.Stage() and populate the application-supplied USD with population.open_usd(stage, scene_path, ordinal=1, domains=PopulationDomain.ALL). Seal population with stage.advance_write_floor(1).wait() before importing. If the application already supplies a populated stage, reuse it and its sealed ordinal; do not reload the scene or assume its ordinal is 1.
  2. Create an empty newton.ModelBuilder(). Configure defaults and register any solver-owned custom attributes before calling ovnewton.add_ovstage(builder, stage, ordinal=population_ordinal). Compose all scene assets into one ovstage first: this entry point currently requires a builder without model entities and supports one stage per builder.
  3. For MuJoCo, register SolverMuJoCo.register_custom_attributes(builder) before calling ovnewton.add_ovstage(). For rigid-body VBD, register SolverVBD.register_custom_attributes(builder) before ovnewton.add_ovstage() and call builder.color() after that import, before finalization. Use SolverVBD(model, rigid_compliant_alm=True) for compliant rigid-body contacts, following the example's solver settings and contact-material tuning.
  4. Finalize with builder.finalize(skip_validation_joints=import_result.has_orphan_joints), where import_result is the result of add_ovstage. Construct the solver and bind with ovnewton.attach_ovstage(stage, model=model, ordinal=population_ordinal). attach_ovstage(stage) is the convenience path when no builder customization is needed. When binding an existing model, body and joint labels must match stage paths.

Step and synchronize

Allocate two model states, controls, and contacts. Each substep clears forces, computes contacts, calls the solver, and swaps the states. Start from the example's collision pipeline and solver configuration rather than assuming every solver has identical preparation requirements.

After stepping, publish the current state with binding.update_to_ovstage(state, ordinal=output_ordinal), then seal it with stage.advance_write_floor(output_ordinal).wait(). Coordinate increasing write ordinals with the application's other stage writers.

To consume application edits, seal them first and call binding.update_from_ovstage(state, control) before stepping, using the same control passed to the solver. This reads the latest sealed supported state and drive-target fields. An explicit read ordinal is a consistency ceiling, not historical playback. Selected Newton-native output can instead be read through binding.query() and binding.read() without stage publication.

For rendering, publish and seal Newton output before the renderer consumes the stage. Newton's simulation device and OVRTX's rendering device are independent; follow the example's synchronization and device-selection options.

Check the support guide before promising support for authored physics. Unsupported physics may fail attachment; do not silently replace it with a different physical model. See the concepts guide and output-read guide for synchronization, diagnostics, read layouts, and lifetimes.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.

中文简介正在准备中。当前显示原文说明。

NVIDIA/skills36652026年10月20日 更新

Customize NVIDIA Nemotron Voice Agent's Generic Pipecat example for healthcare appointment, five-field patient intake, or custom tool-calling workflows without a separate backend.

中文简介正在准备中。当前显示原文说明。

NVIDIA/skills36652026年10月20日 更新

Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras; VIOS records clips, AMC ingests them, then runs calibration.

中文简介正在准备中。当前显示原文说明。

NVIDIA/skills36652026年10月20日 更新

Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.

中文简介正在准备中。当前显示原文说明。

NVIDIA/skills36652026年10月20日 更新

Calibrates pre-recorded `cam_*.mp4` datasets through the AutoMagicCalib REST API. Use for user-supplied local MP4s; route live RTSP streams to `amc-run-rtsp-calibration`.

中文简介正在准备中。当前显示原文说明。

NVIDIA/skills36652026年10月20日 更新

Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API key.

中文简介正在准备中。当前显示原文说明。

NVIDIA/skills36652026年10月20日 更新

查看 NVIDIA 的全部技能

报告此技能的问题