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## Checklist
- [x] I have read and understood the [contribution
guidelines](https://isaac-sim.github.io/IsaacLab/main/source/refs/contributing.html)
- [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
- [x] I have added tests that prove my fix is effective or that my
feature works
- [x] 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
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Most RL libraries expect their own variation of an environment interface. This means the
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data types needed by each library differs. Isaac Lab provides its own wrappers to convert
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the environment into the expected interface by the RL library a user wants to use. These are
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specified in the `Isaac Lab utils wrapper module <https://isaac-sim.github.io/IsaacLab/main/source/api/lab_tasks/isaaclab_rl.html#module-isaaclab_rl>`__.
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specified in :class:`isaaclab_rl`
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See the `full list <https://gymnasium.farama.org/api/wrappers/#gymnasium.Wrapper>`__ of other wrappers APIs. For more information on how these wrappers work,
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please refer to the `Wrapping environments <https://isaac-sim.github.io/IsaacLab/main/source/how-to/wrap_rl_env.html#how-to-env-wrappers>`__ documentation.
@@ -345,7 +347,7 @@ Check out our resources on using Isaac Lab with your robots.
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Review Our Documentation & Samples Resources
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* `Isaac Lab Tutorials`_
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* :ref:`Isaac Lab Tutorials<tutorials>`
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* `Fast-Track Robot Learning in Simulation Using NVIDIA Isaac Lab`_
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* `Supercharge Robotics Workflows with AI and Simulation Using NVIDIA Isaac Sim 4.0 and NVIDIA Isaac Lab`_
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* `Closing the Sim-to-Real Gap: Training Spot Quadruped Locomotion with NVIDIA Isaac Lab <https://developer.nvidia.com/blog/closing-the-sim-to-real-gap-training-spot-quadruped-locomotion-with-nvidia-isaac-lab/>`__
@@ -360,16 +362,15 @@ Learn More About Featured NVIDIA Solutions
.. _Scale AI-Enabled Robotics Development Workloads with NVIDIA OSMO: https://developer.nvidia.com/blog/scale-ai-enabled-robotics-development-workloads-with-nvidia-osmo/
.. _Fast-Track Robot Learning in Simulation Using NVIDIA Isaac Lab: https://developer.nvidia.com/blog/fast-track-robot-learning-in-simulation-using-nvidia-isaac-lab/
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.. _Supercharge Robotics Workflows with AI and Simulation Using NVIDIA Isaac Sim 4.0 and NVIDIA Isaac Lab: https://developer.nvidia.com/blog/supercharge-robotics-workflows-with-ai-and-simulation-using-nvidia-isaac-sim-4-0-and-nvidia-isaac-lab/
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@@ -6,7 +6,7 @@ Adding a New Robot to Isaac Lab
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.. currentmodule:: isaaclab
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Simulating and training a new robot is a multi-step process that starts with importing the robot into Isaac Sim.
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This is covered in depth in the Isaac Sim documentation `here <https://docs.isaacsim.omniverse.nvidia.com/latest/robot_setup/importers_exporters.html>`_.
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This is covered in depth in the Isaac Sim documentation `here <https://docs.isaacsim.omniverse.nvidia.com/latest/importer_exporter/importers_exporters.html>`_.
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Once the robot is imported and tuned for simulation, we must define those interfaces necessary to clone the robot across multiple environments, drive its joints,
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and properly reset it, regardless of the chosen workflow or training framework.
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