Updates code for release 1.3.0 (#1444)

# Description

Updates code for release 1.3.0

---------

Signed-off-by: Kelly Guo <[email protected]>
Co-authored-by: David Hoeller <[email protected]>

Author: kellyguo11

README.md

@@ -13,13 +13,28 @@
 [![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
 

VERSION

@@ -1 +1 @@
-1.2.0
+1.3.0

docs/source/overview/reinforcement-learning/rl_existing_scripts.rst

@@ -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
@@ -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
 ----
@@ -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
@@ -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>``

source/apps/isaaclab.python.headless.kit

@@ -5,7 +5,7 @@
 [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"]

source/apps/isaaclab.python.headless.rendering.kit

@@ -9,7 +9,7 @@
 [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"]

source/apps/isaaclab.python.kit

@@ -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"]

source/apps/isaaclab.python.rendering.kit

@@ -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"]