add cloud simulation docs: nvidia brev.

.gitmodules

@@ -0,0 +1,3 @@
+[submodule "dependencies/IsaacLab"]
+	path = dependencies/IsaacLab
+	url = https://github.com/isaac-sim/IsaacLab.git

docs/docs/docs/cloud_simulation/nvidia_brev.md

@@ -0,0 +1,38 @@
+# Experience LeIsaac with NVIDIA Brev
+
+The fastest way to get started with LeIsaac — you don't need a high-performance GPU, just a web browser.
+
+Open a web browser and navigate to this [link](https://brev.nvidia.com/launchable/deploy/now?launchableID=env-35P96N3pyzVDW3Xlohy7X2TuLCX). After the deployment is complete, click the link for port 80 (HTTP) to open Visual Studio Code Server. The default password is `password`.
+
+Quick install:
+```bash
+cd leisaac
+pip install -e source/leisaac
+```
+
+Our four open-source scenarios have been pre-installed and can be started using the following command:
+```bash
+python scripts/environments/teleoperation/teleop_se3_agent.py \
+    --task=LeIsaac-SO101-PickOrange-v0 \
+    --teleop_device=keyboard \
+    --num_envs=1 \
+    --device=cuda \
+    --enable_cameras \
+    --kit_args="--no-window --enable omni.kit.livestream.webrtc"
+```
+
+Then you can open a new browser tab to view the UI. In this tab, paste the same address as the Visual Studio Code server, changing the end of the URL to `/viewer`.
+
+:::info[Example]
+If VS Code Server is at `ec2.something.amazonaws.com`, then the UI can be accessed at `ec2.something.amazonaws.com/viewer`.
+:::
+
+After a few seconds you should see the UI in the viewer tab. The first launch may take much longer as shaders are cached.
+
+Here is our demo video:
+
+<video
+  controls
+  src="https://github.com/user-attachments/assets/35228eb4-6e2f-4dc1-b066-fff616ca4505"
+  style={{ width: '100%', maxWidth: '960px', borderRadius: '8px' }}
+/>

docs/docs/docs/getting_started/installation.md

@@ -2,33 +2,42 @@
 
 ## 1. Environment Setup
 
-First, follow the [IsaacLab official installation guide](https://isaac-sim.github.io/IsaacLab/main/source/setup/installation/index.html) to install IsaacLab. We recommend using Conda for easier environment management. In summary, you only need to run the following command.
+First, clone our repository and related submodules.
+
+```bash
+git clone https://github.com/LightwheelAI/leisaac.git --recursive
+```
+
+Then follow the [IsaacLab official installation guide](https://isaac-sim.github.io/IsaacLab/main/source/setup/installation/index.html) to install IsaacLab. We recommend using Conda for easier environment management. In summary, you only need to run the following command.
 
 ```bash
 # Create and activate environment
-conda create -n leisaac python=3.10
+conda create -n leisaac python=3.11
 conda activate leisaac
 
 # Install cuda-toolkit
-conda install -c "nvidia/label/cuda-11.8.0" cuda-toolkit
+conda install -c "nvidia/label/cuda-12.8.1" cuda-toolkit
 
 # Install PyTorch
-pip install torch==2.5.1 torchvision==0.20.1 --index-url https://download.pytorch.org/whl/cu118
+pip install -U torch==2.7.0 torchvision==0.22.0 --index-url https://download.pytorch.org/whl/cu128
 
 # Install IsaacSim
 pip install --upgrade pip
-pip install 'isaacsim[all,extscache]==4.5.0' --extra-index-url https://pypi.nvidia.com
+pip install "isaacsim[all,extscache]==5.1.0" --extra-index-url https://pypi.nvidia.com
 
 # Install IsaacLab
-git clone git@github.com:isaac-sim/IsaacLab.git
 sudo apt install cmake build-essential
 
-cd IsaacLab
-# fix isaaclab version for isaacsim4.5
-git checkout v2.1.1
+cd dependencies/IsaacLab
 ./isaaclab.sh --install
 ```
 
+Finally, install leisaac as dependency.
+```bash
+cd ../..
+pip install -e source/leisaac
+```
+
 ::::tip
 The steps above are essentially the same as the official IsaacLab documentation; please adjust according to the versions you use. Below is the compatibility between LeIsaac and IsaacLab and the related version dependencies. 
 
@@ -42,18 +51,7 @@ If you are using a 50-series GPU, we recommend using IsaacSim 5.0+ and IsaacLab
 | PyTorch    | 2.5.1       | 2.7.0      | 2.7.0       |
 ::::
 
-## 2. Clone LeIsaac Repository and Install
-
-Clone our repository and install it as dependency.
-
-```bash
-cd ..
-git clone https://github.com/LightwheelAI/leisaac.git
-cd leisaac
-pip install -e source/leisaac
-```
-
-## 3. Asset Preparation
+## 2. Asset Preparation
 
 We provide an example USD asset—a kitchen scene. Please download related scene [here](https://github.com/LightwheelAI/leisaac/releases/tag/v0.1.0) and extract it into the `assets` directory. The directory structure should look like this:
 
@@ -83,7 +81,7 @@ Below are the download links for the scenes we provide. For more high-quality sc
 | Lightwheel Bedroom   | Realistic bedroom scene with cloth | [Download](https://github.com/LightwheelAI/leisaac/releases/tag/v0.2.0)                  |
 ::::
 
-## 4. Device Setup 
+## 3. Device Setup 
 
 We use the SO101Leader as the teleoperation device. Please follow the [official documentation](https://huggingface.co/docs/lerobot/so101) for connection and configuration.
 

docs/sidebars.js

@@ -78,6 +78,24 @@ const sidebars = {
       ],
     },
     'docs/trouble_shooting',
+    {
+      type: 'category',
+      label: 'Cloud Simulation',
+      link: {
+        type: 'generated-index',
+        slug: '/docs/cloud_simulation', 
+        title: 'Cloud Simulation', 
+        description: 'Using LeIsaac on cloud platforms.'
+      },
+      items: [
+        {
+          type: 'category',
+          label: 'NVIDIA Brev',
+          link: { type: 'doc', id: 'docs/cloud_simulation/nvidia_brev' },
+          items: [],
+        },
+      ],
+    },
   ],
 
   resources: [