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Updates code for release 1.3.0 (isaac-sim#1444)
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# Description

Updates code for release 1.3.0

---------

Signed-off-by: Kelly Guo <[email protected]>
Co-authored-by: David Hoeller <[email protected]>
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kellyguo11 and Dhoeller19 authored Nov 21, 2024
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27 changes: 21 additions & 6 deletions README.md
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[![License](https://img.shields.io/badge/license-BSD--3-yellow.svg)](https://opensource.org/licenses/BSD-3-Clause)


**Isaac Lab** is a unified and modular framework for robot learning that aims to simplify common workflows
in robotics research (such as RL, learning from demonstrations, and motion planning). It is built upon
[NVIDIA Isaac Sim](https://docs.omniverse.nvidia.com/isaacsim/latest/overview.html) to leverage the latest
simulation capabilities for photo-realistic scenes and fast and accurate simulation.
**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 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.

## Key Features

Isaac Lab offers a comprehensive set of tools and environments designed to facilitate robot learning:
- **Robots**: A diverse collection of robots, from manipulators, quadrupeds, to humanoids, with 16 commonly available models.
- **Environments**: Ready-to-train implementations of more than 30 environments, which can be trained with popular reinforcement learning frameworks such as RSL RL, SKRL, RL Games, or Stable Baselines. We also support multi-agent reinforcement learning.
- **Physics**: Rigid bodies, articulated systems, deformable objects
- **Sensors**: RGB/depth/segmentation cameras, camera annotations, IMU, contact sensors, ray casters.


## Getting Started

Our [documentation page](https://isaac-sim.github.io/IsaacLab) provides everything you need to get started, including detailed tutorials and step-by-step guides. Follow these links to learn more about:

- [Installation steps](https://isaac-sim.github.io/IsaacLab/main/source/setup/installation/index.html#local-installation)
- [Reinforcement learning](https://isaac-sim.github.io/IsaacLab/main/source/overview/reinforcement-learning/rl_existing_scripts.html)
- [Tutorials](https://isaac-sim.github.io/IsaacLab/main/source/tutorials/index.html)
- [Available environments](https://isaac-sim.github.io/IsaacLab/main/source/overview/environments.html)

Please refer to our [documentation page](https://isaac-sim.github.io/IsaacLab) to learn more about the
installation steps, features, tutorials, and how to set up your project with Isaac Lab.

## Contributing to Isaac Lab

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2 changes: 1 addition & 1 deletion VERSION
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@@ -1 +1 @@
1.2.0
1.3.0
133 changes: 67 additions & 66 deletions docs/source/overview/reinforcement-learning/rl_existing_scripts.rst
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Expand Up @@ -4,12 +4,12 @@ Reinforcement Learning Wrappers
We provide wrappers to different reinforcement libraries. These wrappers convert the data
from the environments into the respective libraries function argument and return types.

Stable-Baselines3
-----------------

RL-Games
--------

- Training an agent with
`Stable-Baselines3 <https://stable-baselines3.readthedocs.io/en/master/index.html>`__
on ``Isaac-Cartpole-v0``:
`RL-Games <https://github.com/Denys88/rl_games>`__ on ``Isaac-Ant-v0``:

.. tab-set::
:sync-group: os
Expand All @@ -19,30 +19,65 @@ Stable-Baselines3

.. code:: bash
# install python module (for stable-baselines3)
./isaaclab.sh -i sb3
# install python module (for rl-games)
./isaaclab.sh -i rl_games
# run script for training
# note: we set the device to cpu since SB3 doesn't optimize for GPU anyway
./isaaclab.sh -p source/standalone/workflows/sb3/train.py --task Isaac-Cartpole-v0 --headless --device cpu
./isaaclab.sh -p source/standalone/workflows/rl_games/train.py --task Isaac-Ant-v0 --headless
# run script for playing with 32 environments
./isaaclab.sh -p source/standalone/workflows/sb3/play.py --task Isaac-Cartpole-v0 --num_envs 32 --checkpoint /PATH/TO/model.zip
./isaaclab.sh -p source/standalone/workflows/rl_games/play.py --task Isaac-Ant-v0 --num_envs 32 --checkpoint /PATH/TO/model.pth
# run script for recording video of a trained agent (requires installing `ffmpeg`)
./isaaclab.sh -p source/standalone/workflows/sb3/play.py --task Isaac-Cartpole-v0 --headless --video --video_length 200
./isaaclab.sh -p source/standalone/workflows/rl_games/play.py --task Isaac-Ant-v0 --headless --video --video_length 200
.. tab-item:: :icon:`fa-brands fa-windows` Windows
:sync: windows

.. code:: batch
:: install python module (for stable-baselines3)
isaaclab.bat -i sb3
:: install python module (for rl-games)
isaaclab.bat -i rl_games
:: run script for training
:: note: we set the device to cpu since SB3 doesn't optimize for GPU anyway
isaaclab.bat -p source\standalone\workflows\sb3\train.py --task Isaac-Cartpole-v0 --headless --device cpu
isaaclab.bat -p source\standalone\workflows\rl_games\train.py --task Isaac-Ant-v0 --headless
:: run script for playing with 32 environments
isaaclab.bat -p source\standalone\workflows\sb3\play.py --task Isaac-Cartpole-v0 --num_envs 32 --checkpoint /PATH/TO/model.zip
isaaclab.bat -p source\standalone\workflows\rl_games\play.py --task Isaac-Ant-v0 --num_envs 32 --checkpoint /PATH/TO/model.pth
:: run script for recording video of a trained agent (requires installing `ffmpeg`)
isaaclab.bat -p source\standalone\workflows\sb3\play.py --task Isaac-Cartpole-v0 --headless --video --video_length 200
isaaclab.bat -p source\standalone\workflows\rl_games\play.py --task Isaac-Ant-v0 --headless --video --video_length 200
RSL-RL
------

- Training an agent with
`RSL-RL <https://github.com/leggedrobotics/rsl_rl>`__ on ``Isaac-Reach-Franka-v0``:

.. tab-set::
:sync-group: os

.. tab-item:: :icon:`fa-brands fa-linux` Linux
:sync: linux

.. code:: bash
# install python module (for rsl-rl)
./isaaclab.sh -i rsl_rl
# run script for training
./isaaclab.sh -p source/standalone/workflows/rsl_rl/train.py --task Isaac-Reach-Franka-v0 --headless
# run script for playing with 32 environments
./isaaclab.sh -p source/standalone/workflows/rsl_rl/play.py --task Isaac-Reach-Franka-v0 --num_envs 32 --load_run run_folder_name --checkpoint model.pt
# run script for recording video of a trained agent (requires installing `ffmpeg`)
./isaaclab.sh -p source/standalone/workflows/rsl_rl/play.py --task Isaac-Reach-Franka-v0 --headless --video --video_length 200
.. tab-item:: :icon:`fa-brands fa-windows` Windows
:sync: windows

.. code:: batch
:: install python module (for rsl-rl)
isaaclab.bat -i rsl_rl
:: run script for training
isaaclab.bat -p source\standalone\workflows\rsl_rl\train.py --task Isaac-Reach-Franka-v0 --headless
:: run script for playing with 32 environments
isaaclab.bat -p source\standalone\workflows\rsl_rl\play.py --task Isaac-Reach-Franka-v0 --num_envs 32 --load_run run_folder_name --checkpoint model.pt
:: run script for recording video of a trained agent (requires installing `ffmpeg`)
isaaclab.bat -p source\standalone\workflows\rsl_rl\play.py --task Isaac-Reach-Franka-v0 --headless --video --video_length 200
SKRL
----
Expand Down Expand Up @@ -129,48 +164,12 @@ SKRL
:: run script for playing with 32 environments with the MAPPO algorithm (IPPO is also supported)
isaaclab.bat -p source\standalone\workflows\skrl\play.py --task Isaac-Shadow-Hand-Over-Direct-v0 --num_envs 32 --algorithm MAPPO --checkpoint /PATH/TO/model.pt
RL-Games
--------

- Training an agent with
`RL-Games <https://github.com/Denys88/rl_games>`__ on ``Isaac-Ant-v0``:

.. tab-set::
:sync-group: os

.. tab-item:: :icon:`fa-brands fa-linux` Linux
:sync: linux

.. code:: bash
# install python module (for rl-games)
./isaaclab.sh -i rl_games
# run script for training
./isaaclab.sh -p source/standalone/workflows/rl_games/train.py --task Isaac-Ant-v0 --headless
# run script for playing with 32 environments
./isaaclab.sh -p source/standalone/workflows/rl_games/play.py --task Isaac-Ant-v0 --num_envs 32 --checkpoint /PATH/TO/model.pth
# run script for recording video of a trained agent (requires installing `ffmpeg`)
./isaaclab.sh -p source/standalone/workflows/rl_games/play.py --task Isaac-Ant-v0 --headless --video --video_length 200
.. tab-item:: :icon:`fa-brands fa-windows` Windows
:sync: windows

.. code:: batch
:: install python module (for rl-games)
isaaclab.bat -i rl_games
:: run script for training
isaaclab.bat -p source\standalone\workflows\rl_games\train.py --task Isaac-Ant-v0 --headless
:: run script for playing with 32 environments
isaaclab.bat -p source\standalone\workflows\rl_games\play.py --task Isaac-Ant-v0 --num_envs 32 --checkpoint /PATH/TO/model.pth
:: run script for recording video of a trained agent (requires installing `ffmpeg`)
isaaclab.bat -p source\standalone\workflows\rl_games\play.py --task Isaac-Ant-v0 --headless --video --video_length 200
RSL-RL
------
Stable-Baselines3
-----------------

- Training an agent with
`RSL-RL <https://github.com/leggedrobotics/rsl_rl>`__ on ``Isaac-Reach-Franka-v0``:
`Stable-Baselines3 <https://stable-baselines3.readthedocs.io/en/master/index.html>`__
on ``Isaac-Cartpole-v0``:

.. tab-set::
:sync-group: os
Expand All @@ -180,28 +179,30 @@ RSL-RL

.. code:: bash
# install python module (for rsl-rl)
./isaaclab.sh -i rsl_rl
# install python module (for stable-baselines3)
./isaaclab.sh -i sb3
# run script for training
./isaaclab.sh -p source/standalone/workflows/rsl_rl/train.py --task Isaac-Reach-Franka-v0 --headless
# note: we set the device to cpu since SB3 doesn't optimize for GPU anyway
./isaaclab.sh -p source/standalone/workflows/sb3/train.py --task Isaac-Cartpole-v0 --headless --device cpu
# run script for playing with 32 environments
./isaaclab.sh -p source/standalone/workflows/rsl_rl/play.py --task Isaac-Reach-Franka-v0 --num_envs 32 --load_run run_folder_name --checkpoint model.pt
./isaaclab.sh -p source/standalone/workflows/sb3/play.py --task Isaac-Cartpole-v0 --num_envs 32 --checkpoint /PATH/TO/model.zip
# run script for recording video of a trained agent (requires installing `ffmpeg`)
./isaaclab.sh -p source/standalone/workflows/rsl_rl/play.py --task Isaac-Reach-Franka-v0 --headless --video --video_length 200
./isaaclab.sh -p source/standalone/workflows/sb3/play.py --task Isaac-Cartpole-v0 --headless --video --video_length 200
.. tab-item:: :icon:`fa-brands fa-windows` Windows
:sync: windows

.. code:: batch
:: install python module (for rsl-rl)
isaaclab.bat -i rsl_rl
:: install python module (for stable-baselines3)
isaaclab.bat -i sb3
:: run script for training
isaaclab.bat -p source\standalone\workflows\rsl_rl\train.py --task Isaac-Reach-Franka-v0 --headless
:: note: we set the device to cpu since SB3 doesn't optimize for GPU anyway
isaaclab.bat -p source\standalone\workflows\sb3\train.py --task Isaac-Cartpole-v0 --headless --device cpu
:: run script for playing with 32 environments
isaaclab.bat -p source\standalone\workflows\rsl_rl\play.py --task Isaac-Reach-Franka-v0 --num_envs 32 --load_run run_folder_name --checkpoint model.pt
isaaclab.bat -p source\standalone\workflows\sb3\play.py --task Isaac-Cartpole-v0 --num_envs 32 --checkpoint /PATH/TO/model.zip
:: run script for recording video of a trained agent (requires installing `ffmpeg`)
isaaclab.bat -p source\standalone\workflows\rsl_rl\play.py --task Isaac-Reach-Franka-v0 --headless --video --video_length 200
isaaclab.bat -p source\standalone\workflows\sb3\play.py --task Isaac-Cartpole-v0 --headless --video --video_length 200
All the scripts above log the training progress to `Tensorboard`_ in the ``logs`` directory in the root of
the repository. The logs directory follows the pattern ``logs/<library>/<task>/<date-time>``, where ``<library>``
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2 changes: 1 addition & 1 deletion source/apps/isaaclab.python.headless.kit
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[package]
title = "Isaac Lab Python Headless"
description = "An app for running Isaac Lab headlessly"
version = "1.2.0"
version = "1.3.0"

# That makes it browsable in UI with "experience" filter
keywords = ["experience", "app", "isaaclab", "python", "headless"]
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2 changes: 1 addition & 1 deletion source/apps/isaaclab.python.headless.rendering.kit
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[package]
title = "Isaac Lab Python Headless Camera"
description = "An app for running Isaac Lab headlessly with rendering enabled"
version = "1.2.0"
version = "1.3.0"

# That makes it browsable in UI with "experience" filter
keywords = ["experience", "app", "isaaclab", "python", "camera", "minimal"]
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2 changes: 1 addition & 1 deletion source/apps/isaaclab.python.kit
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Expand Up @@ -5,7 +5,7 @@
[package]
title = "Isaac Lab Python"
description = "An app for running Isaac Lab"
version = "1.2.0"
version = "1.3.0"

# That makes it browsable in UI with "experience" filter
keywords = ["experience", "app", "usd"]
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2 changes: 1 addition & 1 deletion source/apps/isaaclab.python.rendering.kit
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Expand Up @@ -9,7 +9,7 @@
[package]
title = "Isaac Lab Python Camera"
description = "An app for running Isaac Lab with rendering enabled"
version = "1.2.0"
version = "1.3.0"

# That makes it browsable in UI with "experience" filter
keywords = ["experience", "app", "isaaclab", "python", "camera", "minimal"]
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