brax
mujoco
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brax | mujoco | |
---|---|---|
11 | 20 | |
2,058 | 7,159 | |
3.3% | 4.0% | |
5.2 | 9.8 | |
10 days ago | 6 days ago | |
Jupyter Notebook | C++ | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
brax
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4000x Speedup in Reinforcement Learning with Jax
There is Brax with its Ant, Humanoid and other rigid body articulated Gym environments: https://github.com/google/brax
- Physic engine for 3D simulation: which one to use?
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Brax vs TDS for differentiable rigid body dynamics
I need differentiable rigid body dynamics because I want to do nonlinear MPC. One library that can do this is C++ is Tiny Differentiable Simulator https://github.com/erwincoumans/tiny-differentiable-simulator. As I understand it, this software uses a C++ auto-diff library and code generation to create CUDA kernels to compute fast derivatives in parallel. This seems pretty fast because it's C++. Another option is Brax https://github.com/google/brax. Brax uses JAX which I've never used, but from what I've seen online, JAX is popular for researchers and probably very good.
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Deep learning for robotics
I am doing a MSc on robotics with a focus on machine learning, especially attention based architectures. There is a lot simulation and reinforcement learning going on. I have a funding of ~2500$ for the hardware system (no flexibility here, cannot use it for cloud either). I used pcpartpicker.com to select compatible components, as shown below. I am not located in the western part of the world; which means I have difficulty accessing some components and prices are higher here than that of pcpartpicker.com. That is why I am aiming towards 2000 - 2200$ range in the pcpartpicker.com. - Overall, what do you think of my planned setup? - Since there is a lot of simulation planned including rigid body dynamics with contact (libraries like https://github.com/raisimTech/raisimLib, https://github.com/deepmind/mujoco), I need some powerful CPU to use these libraries. I know that Intel has MKL over AMD; however, I am not sure how relevant that is for my case. The robotics simulators are generally written with C++, uses Eigen or their own math libraries. I feel like there is a lot of linear algebra involved and Intel combined with MKL should give me less headache. I have chosen i9-12900K, but what about AMD Ryzen9 5950X for example? - There is a new generation of rigid body simulators which use GPU instead of CPU (https://github.com/google/brax, https://developer.nvidia.com/isaac-gym). I do not think they are as mature as the previously mentioned simulators. Perhaps I am mistaken. Shall I focus on them instead? In terms of hardware that means I can downgrade the CPU to Ryzen5, and upgrade to RTX3080, roughly. - Do you think this system is easy to upgrade in future? What can I change to make it easier for long-term use and upgrades? Thanks for any help!
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[D] Advice on Hardware Setup for Robotics
There is a new generation of rigid body simulators which use GPU instead of CPU (https://github.com/google/brax, https://developer.nvidia.com/isaac-gym). I do not think they are as mature as the previously mentioned simulators. Perhaps I am mistaken. Shall I focus on them instead? In terms of hardware that means I can downgrade the CPU to Ryzen5, and upgrade to RTX3080, roughly.
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DeepMind open-sourcing MuJoCo simulator
I wonder what this means for the future of Brax [1].
1. https://github.com/google/brax
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Any tutorial on how to create RL C++ environments?
If you want raw speed, parallel execution on GPU or TPU is best. Checkout out our Brax simulator, which uses the XLA compiler and JAX Python frontend: https://github.com/google/brax
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Best environment to train RL agents
Check out Brax, hardware accelerated RL training in a Google Jupyter Colab. It trains typical RL tasks in minutes on TPU, also on GPU or CPU. And it is free, you can train with just a browser: https://github.com/google/brax
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[N] Mujoco is free for everyone until October 31 2021
Anyone made any progress with Brax? That was sold as a massively-parallel Mujoco alternative but not sure if anyone's actually using it yet.
- [R] Brax: A Differentiable Physics Engine for Large Scale Rigid Body Simulation, with a focus on performance and parallelism on accelerators, written in JAX.
mujoco
- MuJoCo 3
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Mujoco Question
I have installed mujoco-2.3.5-window-x86_64.zip and Source Code (zip) in https://github.com/deepmind/mujoco/releases. From download file, I extracted file and clicked simulate (mujoco-2.3.5-window-x86_6 -> bin); however it shows black screen. I am not sure what I am doing wrong.
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Python Tutorials
Best place for technical MuJoCo questions is our GitHub repo (https://github.com/deepmind/mujoco) -- our entire team is notified for each issue posted there.
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Mujoco + Unity => setting transform
Could you please post this question on https://github.com/deepmind/mujoco also? You'd me more likely to get an answer there since most of our team don't track Reddit questions.
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Hi, i guys i have been working on bouncing ball experiment in Mujoco and i have had a fairly realistic effect of a ball bouncing, however i want it to be bouncing forward like tossing ball and it bounces forward? how can i achieve this? my XML is below
Could you please post this as an issue on https://github.com/deepmind/mujoco ?
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MuJoCo Soft Surface Problem
Try posting in https://github.com/deepmind/mujoco/discussions ?
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Deep RL with Mujoco environments using Docker on Apple Silicon
Not really. You can use conda or pip to install prebuilt mujoco packages that also include glfw. Check out https://github.com/deepmind/mujoco/blob/main/python/README.md
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DeepMind's open-source version of MuJoCo available on GitHub
MuJoCo Github link
- MuJoCo Physics
- DeepMind open-sources MuJoCo Physics
What are some alternatives?
pybullet-gym - Open-source implementations of OpenAI Gym MuJoCo environments for use with the OpenAI Gym Reinforcement Learning Research Platform.
gazebo-classic - Gazebo classic. For the latest version, see https://github.com/gazebosim/gz-sim
tiny-differentiable-simulator - Tiny Differentiable Simulator is a header-only C++ and CUDA physics library for reinforcement learning and robotics with zero dependencies.
Bullet - Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
CHRONO - High-performance C++ library for multiphysics and multibody dynamics simulations
RustyNEAT - Rust implementation of NEAT algorithm (HyperNEAT + ES-HyperNEAT + NoveltySearch + CTRNN + L-systems)
sofa - Real-time multi-physics simulation with an emphasis on medical simulation.
open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
LiquidFun - 2D physics engine for games
Numba - NumPy aware dynamic Python compiler using LLVM
Box2D - Box2D is a 2D physics engine for games