Updates the script path in the document (#1766)

# Description

Update the script path in the document

Fixes #1762 

## Type of change

- Bug fix (non-breaking change which fixes an issue)
- This change requires a documentation update

## Checklist

- [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with
`./isaaclab.sh --format`
- [x] I have made corresponding changes to the documentation
- [x] My changes generate no new warnings
- [ ] I have added tests that prove my fix is effective or that my
feature works
- [ ] I have updated the changelog and the corresponding version in the
extension's `config/extension.toml` file
- [x] I have added my name to the `CONTRIBUTORS.md` or my name already
exists there

README.md

@@ -4,7 +4,7 @@
 
 # Isaac Lab
 
-[![IsaacSim](https://img.shields.io/badge/IsaacSim-4.5.0-silver.svg)](https://docs.omniverse.nvidia.com/isaacsim/latest/overview.html)
+[![IsaacSim](https://img.shields.io/badge/IsaacSim-4.5.0-silver.svg)](https://docs.isaacsim.omniverse.nvidia.com/latest/index.html)
 [![Python](https://img.shields.io/badge/python-3.10-blue.svg)](https://docs.python.org/3/whatsnew/3.10.html)
 [![Linux platform](https://img.shields.io/badge/platform-linux--64-orange.svg)](https://releases.ubuntu.com/20.04/)
 [![Windows platform](https://img.shields.io/badge/platform-windows--64-orange.svg)](https://www.microsoft.com/en-us/)
@@ -14,7 +14,7 @@
 [![License](https://img.shields.io/badge/license-Apache--2.0-yellow.svg)](https://opensource.org/license/apache-2-0)
 
 
-**Isaac Lab** is a GPU-accelerated, open-source framework designed to unify and simplify robotics research workflows, such as reinforcement learning, imitation learning, and motion planning. Built on [NVIDIA Isaac Sim](https://docs.omniverse.nvidia.com/isaacsim/latest/overview.html), it combines fast and accurate physics and sensor simulation, making it an ideal choice for sim-to-real transfer in robotics.
+**Isaac Lab** is a GPU-accelerated, open-source framework designed to unify and simplify robotics research workflows, such as reinforcement learning, imitation learning, and motion planning. Built on [NVIDIA Isaac Sim](https://docs.isaacsim.omniverse.nvidia.com/latest/index.html), it combines fast and accurate physics and sensor simulation, making it an ideal choice for sim-to-real transfer in robotics.
 
 Isaac Lab provides developers with a range of essential features for accurate sensor simulation, such as RTX-based cameras, LIDAR, or contact sensors. The framework's GPU acceleration enables users to run complex simulations and computations faster, which is key for iterative processes like reinforcement learning and data-intensive tasks. Moreover, Isaac Lab can run locally or be distributed across the cloud, offering flexibility for large-scale deployments.
 

docs/source/api/lab/isaaclab.app.rst

@@ -111,5 +111,5 @@ Simulation App Launcher
 
 
 .. _livestream: https://docs.omniverse.nvidia.com/app_isaacsim/app_isaacsim/manual_livestream_clients.html
-.. _`Native Livestream`: https://docs.omniverse.nvidia.com/isaacsim/latest/installation/manual_livestream_clients.html#omniverse-streaming-client-deprecated
-.. _`WebRTC Livestream`: https://docs.omniverse.nvidia.com/isaacsim/latest/installation/manual_livestream_clients.html#isaac-sim-short-webrtc-streaming-client
+.. _`Native Livestream`: https://docs.isaacsim.omniverse.nvidia.com/latest/installation/manual_livestream_clients.html#omniverse-streaming-client-deprecated
+.. _`WebRTC Livestream`: https://docs.isaacsim.omniverse.nvidia.com/latest/installation/manual_livestream_clients.html#isaac-sim-short-webrtc-streaming-client

docs/source/deployment/docker.rst

@@ -292,7 +292,7 @@ To run an example within the container, run:
 
 
 .. _`NVIDIA Omniverse EULA`: https://docs.omniverse.nvidia.com/platform/latest/common/NVIDIA_Omniverse_License_Agreement.html
-.. _`container installation`: https://docs.omniverse.nvidia.com/isaacsim/latest/installation/install_container.html
+.. _`container installation`: https://docs.isaacsim.omniverse.nvidia.com/latest/installation/install_container.html
 .. _`Docker website`: https://docs.docker.com/desktop/install/linux-install/
 .. _`docker compose`: https://docs.docker.com/compose/install/linux/#install-using-the-repository
 .. _`NVIDIA Container Toolkit`: https://github.com/NVIDIA/nvidia-container-toolkit
@@ -300,7 +300,7 @@ To run an example within the container, run:
 .. _`post-installation steps`: https://docs.docker.com/engine/install/linux-postinstall/
 .. _`Isaac Sim container`: https://catalog.ngc.nvidia.com/orgs/nvidia/containers/isaac-sim
 .. _`NGC API key`: https://docs.nvidia.com/ngc/gpu-cloud/ngc-user-guide/index.html#generating-api-key
-.. _`several streaming clients`: https://docs.omniverse.nvidia.com/isaacsim/latest/installation/manual_livestream_clients.html
+.. _`several streaming clients`: https://docs.isaacsim.omniverse.nvidia.com/latest/installation/manual_livestream_clients.html
 .. _`known issue`: https://forums.developer.nvidia.com/t/unable-to-use-webrtc-when-i-run-runheadless-webrtc-sh-in-remote-headless-container/222916
 .. _`profile`: https://docs.docker.com/compose/compose-file/15-profiles/
 .. _`apt package`: https://docs.ros.org/en/humble/Installation/Ubuntu-Install-Debians.html#install-ros-2-packages

docs/source/overview/developer-guide/development.rst

@@ -131,8 +131,8 @@ workflow, it is not always possible.
 
 For example, consider robot reinforcement learning. It is essential to have complete control over the simulation step
 and when things update instead of asynchronously waiting for the result. In
-such cases, we require direct control of the simulation, and so it is necessary to write a standalone application. These applications are functionally similar in that they launch the simulator using the :class:`~omni.isaac.lab.app.AppLauncher` and
-then control the simulation directly through the :class:`~omni.isaac.lab.sim.SimulationContext`. In these cases, python modules from extensions **must** be imported after the app is launched.  Doing so before the app is launched will cause missing module errors.
+such cases, we require direct control of the simulation, and so it is necessary to write a standalone application. These applications are functionally similar in that they launch the simulator using the :class:`~isaaclab.app.AppLauncher` and
+then control the simulation directly through the :class:`~isaaclab.sim.SimulationContext`. In these cases, python modules from extensions **must** be imported after the app is launched.  Doing so before the app is launched will cause missing module errors.
 
 The following snippet shows how to write a standalone application:
 

docs/source/setup/installation/binaries_installation.rst

@@ -444,14 +444,14 @@ We recommend adding ``--headless`` for faster training.
 
       .. code:: bash
 
-         ./isaaclab.sh -p source/standalone/workflows/rsl_rl/train.py --task=Isaac-Ant-v0 --headless
+         ./isaaclab.sh -p scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Ant-v0 --headless
 
    .. tab-item:: :icon:`fa-brands fa-windows` Windows
       :sync: windows
 
       .. code:: batch
 
-         isaaclab.bat -p source/standalone/workflows/rsl_rl/train.py --task=Isaac-Ant-v0 --headless
+         isaaclab.bat -p scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Ant-v0 --headless
 
 ... Or a robot dog!
 
@@ -463,14 +463,14 @@ We recommend adding ``--headless`` for faster training.
 
       .. code:: bash
 
-         ./isaaclab.sh -p source/standalone/workflows/rsl_rl/train.py --task=Isaac-Velocity-Rough-Anymal-C-v0 --headless
+         ./isaaclab.sh -p scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Velocity-Rough-Anymal-C-v0 --headless
 
    .. tab-item:: :icon:`fa-brands fa-windows` Windows
       :sync: windows
 
       .. code:: batch
 
-         isaaclab.bat -p source/standalone/workflows/rsl_rl/train.py --task=Isaac-Velocity-Rough-Anymal-C-v0 --headless
+         isaaclab.bat -p scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Velocity-Rough-Anymal-C-v0 --headless
 
 Isaac Lab provides the tools you'll need to create your own **Tasks** and **Workflows** for whatever your project needs may be. Take a look at our :ref:`how-to` guides like `Adding your own learning Library <source/how-to/add_own_library>`_ or `Wrapping Environments <source/how-to/wrap_rl_env>`_ for details.
 

docs/source/setup/installation/pip_installation.rst

@@ -148,7 +148,7 @@ Verifying the Isaac Sim installation
    .. code:: bash
 
       By installing or using Isaac Sim, I agree to the terms of NVIDIA OMNIVERSE LICENSE AGREEMENT (EULA)
-      in https://docs.omniverse.nvidia.com/isaacsim/latest/common/NVIDIA_Omniverse_License_Agreement.html
+      in https://docs.isaacsim.omniverse.nvidia.com/latest/common/NVIDIA_Omniverse_License_Agreement.html
 
       Do you accept the EULA? (Yes/No): Yes
 
@@ -355,14 +355,14 @@ We recommend adding ``--headless`` for faster training.
 
       .. code:: bash
 
-         ./isaaclab.sh -p source/standalone/workflows/rsl_rl/train.py --task=Isaac-Ant-v0 --headless
+         ./isaaclab.sh -p scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Ant-v0 --headless
 
    .. tab-item:: :icon:`fa-brands fa-windows` Windows
       :sync: windows
 
       .. code:: batch
 
-         isaaclab.bat -p source/standalone/workflows/rsl_rl/train.py --task=Isaac-Ant-v0 --headless
+         isaaclab.bat -p scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Ant-v0 --headless
 
 ... Or a robot dog!
 
@@ -374,14 +374,14 @@ We recommend adding ``--headless`` for faster training.
 
       .. code:: bash
 
-         ./isaaclab.sh -p source/standalone/workflows/rsl_rl/train.py --task=Isaac-Velocity-Rough-Anymal-C-v0 --headless
+         ./isaaclab.sh -p scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Velocity-Rough-Anymal-C-v0 --headless
 
    .. tab-item:: :icon:`fa-brands fa-windows` Windows
       :sync: windows
 
       .. code:: batch
 
-         isaaclab.bat -p source/standalone/workflows/rsl_rl/train.py --task=Isaac-Velocity-Rough-Anymal-C-v0 --headless
+         isaaclab.bat -p scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Velocity-Rough-Anymal-C-v0 --headless
 
 Isaac Lab provides the tools you'll need to create your own **Tasks** and **Workflows** for whatever your project needs may be. Take a look at our :ref:`how-to` guides like `Adding your own learning Library <source/how-to/add_own_library>`_ or `Wrapping Environments <source/how-to/wrap_rl_env>`_ for details.