diff --git a/sources/news/20220526 DeepMind-s Open Source MuJoCo Is Available On GitHub.md b/sources/news/20220526 DeepMind-s Open Source MuJoCo Is Available On GitHub.md deleted file mode 100644 index 54f11ea54b..0000000000 --- a/sources/news/20220526 DeepMind-s Open Source MuJoCo Is Available On GitHub.md +++ /dev/null @@ -1,45 +0,0 @@ -[#]: subject: "DeepMind’s Open Source MuJoCo Is Available On GitHub" -[#]: via: "https://www.opensourceforu.com/2022/05/deepminds-open-source-mujoco-is-available-on-github/" -[#]: author: "Laveesh Kocher https://www.opensourceforu.com/author/laveesh-kocher/" -[#]: collector: "lkxed" -[#]: translator: "lkxed" -[#]: reviewer: " " -[#]: publisher: " " -[#]: url: " " - -DeepMind’s Open Source MuJoCo Is Available On GitHub -====== -![deepmind1][1] - -DeepMind, an Alphabet subsidiary and AI research lab, acquired the MuJoCo physics engine for robotics research and development in October 2021. The simulator was to be open-sourced and maintained as a free, open source, community-driven project. DeepMind claims that the open sourcing is now complete, with the entire codebase [available on GitHub][2]. - -MuJoCo, which stands for Multi-Joint Dynamics with Contact, is a physics engine designed to aid research and development in robotics, biomechanics, graphics and animation, and other fields that require fast and accurate simulation. MuJoCo can be used to implement model-based computations for machine learning applications such as control synthesis, state estimation, system identification, mechanism design, data analysis through inverse dynamics, and parallel sampling. It can also be used as a standard simulator, such as for gaming and interactive virtual environments. - -According to DeepMind, the following are some of the features that make MuJoCo appealing for collaboration: - -* Comprehensive simulator capable of simulating complex mechanisms -* Readable, performant, portable code -* Codebase that is easily extensible -* Extensive documentation, including both user-facing and code comments – We hope that colleagues from academia and the OSS community will use this platform and contribute to the codebase, thereby improving research for all. - -DeepMind has more to say: - -“As a C library with no dynamic memory allocation, MuJoCo is very fast. Unfortunately, raw physics speed has historically been hindered by Python wrappers, which made batched, multi-threaded operations non-performant due to the presence of the Global Interpreter Lock (GIL) and non-compiled code. In our roadmap below, we address this issue going forward. - -“For now, we’d like to share some benchmarking results for two common models. The results were obtained on a standard AMD Ryzen 9 5950X machine, running Windows 10.” - --------------------------------------------------------------------------------- - -via: https://www.opensourceforu.com/2022/05/deepminds-open-source-mujoco-is-available-on-github/ - -作者：[Laveesh Kocher][a] -选题：[lkxed][b] -译者：[译者ID](https://github.com/译者ID) -校对：[校对者ID](https://github.com/校对者ID) - -本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出 - -[a]: https://www.opensourceforu.com/author/laveesh-kocher/ -[b]: https://github.com/lkxed -[1]: https://www.opensourceforu.com/wp-content/uploads/2022/05/deepmind1.jpg -[2]: https://github.com/deepmind/mujoco diff --git a/translated/news/20220526 DeepMind-s Open Source MuJoCo Is Available On GitHub.md b/translated/news/20220526 DeepMind-s Open Source MuJoCo Is Available On GitHub.md new file mode 100644 index 0000000000..6830a9eaac --- /dev/null +++ b/translated/news/20220526 DeepMind-s Open Source MuJoCo Is Available On GitHub.md @@ -0,0 +1,60 @@ +[#]: subject: "DeepMind’s Open Source MuJoCo Is Available On GitHub" +[#]: via: "https://www.opensourceforu.com/2022/05/deepminds-open-source-mujoco-is-available-on-github/" +[#]: author: "Laveesh Kocher https://www.opensourceforu.com/author/laveesh-kocher/" +[#]: collector: "lkxed" +[#]: translator: "lkxed" +[#]: reviewer: " " +[#]: publisher: " " +[#]: url: " " + +DeepMind 的开源物理引擎 MuJoCo 已搬至 GitHub +====== +![deepmind1][1] + +DeepMind 是 Alphabet 的子公司和 AI 研究实验室，在 2021 年 10 月，它收购了用于机器人研发的 MuJoCo 物理引擎，并承诺该模拟器将作为免费、开源、社区驱动的项目进行维护。现在，DeepMind 声称开源计划已完成，它的整个代码库 [可在 GitHub 上获得][2]。 + +MuJoCo 是 Multi-Joint Dynamics with Contact 的缩写，它是一个物理引擎，旨在帮助机器人、生物力学、图形和动画等领域的研究和开发（也包括其他需要快速准确模拟的领域）。MuJoCo 可用于帮助机器学习应用实现基于模型的计算，例如控制综合control synthesis、状态估计state estimation、系统识别system identification、机制设计mechanism design、通过逆动力学inverse dynamics来进行数据分析，以及并行采样parallel sampling。它也可以用作标准模拟器，例如用于游戏和交互式虚拟环境。（LCTT 译注：这段话中涉及到不少专业词汇，鉴于译者水平有限，若有谬误，请在评论中指出，同时也欢迎在评论中科普，一起学习～） + +根据 DeepMind 的说法，以下是 MuJoCo 适合协作的一些功能： + +* 能够模拟复杂机制的综合模拟器 +* 可读、高性能、可移植的代码 +* 易于扩展的代码库 +* 丰富的文档，包括面向用户的和代码注释 —— 我们希望学术界和 OSS 社区的同事能够使用这个平台并为代码库做出贡献，从而改善所有人的研究 + +DeepMind 还说： + +> “作为没有动态内存分配的 C 库，MuJoCo 非常快。不幸的是，原始物理速度一直受到 Python 包装器的阻碍：全局解释器锁 (GIL) 和非编译代码的存在，使得批处理、多线程操作无法执行。在下面的路线图中，我们将解决这个问题。” + +（LCTT 译注：原文忘记贴上路线图了，这里补上。） + +路线图： + +* 通过批处理、多线程模拟释放 MuJoCo 的速度潜力 +* 通过改进内部内存管理支持更大的场景 +* 新的增量编译器，带来更好的模型可组合性 +* 通过 Unity 集成支持更好的渲染 +* 对物理导数的原生支持，包括解析和有限差分 + +> “目前，我们想分享两个常见模型的基准测试结果。注意，这个结果是在运行 Windows 10 的标准 AMD Ryzen 9 5950X 机器上获得的。” + +（LCTT 译注：原文忘记贴上测试结果了，这里补上。） + +![基准测试结果][3] + +-------------------------------------------------------------------------------- + +via: https://www.opensourceforu.com/2022/05/deepminds-open-source-mujoco-is-available-on-github/ + +作者：[Laveesh Kocher][a] +选题：[lkxed][b] +译者：[lkxed](https://github.com/lkxed) +校对：[校对者ID](https://github.com/校对者ID) + +本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出 + +[a]: https://www.opensourceforu.com/author/laveesh-kocher/ +[b]: https://github.com/lkxed +[1]: https://www.opensourceforu.com/wp-content/uploads/2022/05/deepmind1.jpg +[2]: https://github.com/deepmind/mujoco +[3]: https://assets-global.website-files.com/621e749a546b7592125f38ed/628b971675cb60d74f5fa189_2A54E864-FE90-49E4-8E58-FE40298303E2.jpeg