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Release Notes

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The release notes are now available in the Isaac Lab GitHub repository. We summarize the release notes here for convenience.

v2.0.2

Overview

This patch release focuses on improving actuator configuration and fixing key bugs while reverting unintended behavioral changes from v2.0.1. We strongly recommend switching to this new version if you’re migrating from a pre-2.0 release of Isaac Lab.

Key Changes:

  • Actuator Limit Handling: Introduced isaaclab.actuators.ActuatorBaseCfg.velocity_limit_sim and isaaclab.actuators.ActuatorBaseCfg.effort_limit_sim to clearly distinguish simulation solver limits from actuator model constraints. Reverted implicit actuator velocity limits to pre-v2.0 behavior
  • Simulation configuration update: Removed isaaclab.sim.SimulationCfg.disable_contact_processing flag to simplify behavior
  • Rendering configuration update: Reverted to pre-2.0 configuration to improve the quality of the render product
  • Tiled camera fixes: Fixed motion vector processing and added a hotfix for retrieving semantic images from the ~isaaclab.sensors.TiledCamera
  • WebRTC Support: Added IP specification for live-streaming

Full Changelog: https://github.com/isaac-sim/IsaacLab/compare/v2.0.1…v2.0.2

New Features

  • Adds isaaclab.actuators.ActuatorBaseCfg.velocity_limit_sim and isaaclab.actuators.ActuatorBaseCfg.effort_limit_sim to actuator.
  • Adds WebRTC livestreaming support with IP specification.

Improvements

  • Adds guidelines and examples for code contribution
  • Separates joint state setters inside Articulation class
  • Implements deterministic evaluation for skrl’s multi-agent algorithms
  • Adds new extensions to pyproject.toml
  • Updates docs on Isaac Sim binary installation path and VSCode integration
  • Removes remaining deprecation warning in RigidObject deprecation
  • Adds security and show&tell notes to documentation
  • Updates docs for segmentation and 50 series GPUs
  • Adds workaround for semantic segmentation issue with tiled camera

Bug Fixes

  • Fixes offset from object obs for Franka stacking env when using parallel envs
  • Adds scene update to ManagerBasedEnv, DirectRLEnv, and MARL envs initialization
  • Loads actuator networks in eval() mode to prevent gradients
  • Fixes instructions on importing ANYmal URDF in docs
  • Fixes setting of root velocities in the event term ~isaaclab.mdp.reset_root_state_from_terrain
  • Fixes activate_contact_sensors when using ~isaaclab.sim.MultiUsdFileCfg
  • Fixes misalignment in motion vectors from ~isaaclab.sim.TiledCamera
  • Sets default tensor device to CPU for Camera rot buffer

Breaking Changes

  • Reverts the setting of joint velocity limits for implicit actuators
  • Removes disable_contact_processing flag from SimulationContext
  • Reverts to old render settings in kit experience files

Migration Guide

We strongly recommend reviewing the details to fully understand the change in behavior, as it may impact the deployment of learned policies. Please open an issue on GitHub if you face any problems.

Introduction of simulation’s effort and velocity limits parameters in ActuatorBaseCfg

We have introduced the configuration variables isaaclab.actuators.ActuatorBaseCfg.velocity_limit_sim and isaaclab.actuators.ActuatorBaseCfg.effort_limit_sim to the isaaclab.actuators.ActuatorBaseCfg to allow users to set the simulation joint velocity and effort limits through the actuator configuration class.

Previously, we were overusing the attributes isaaclab.actuators.ActuatorBaseCfg.velocity_limit and isaaclab.actuators.ActuatorBaseCfg.effort_limit inside the actuator configuration. A series of changes in-between led to a regression from v1.4.0 to v2.0.1 release of IsaacLab. To make this clearer to understand, we note the change in their behavior in a tabular form:

Actuator TypeAttributev1.4.0 Behaviorv2.0.1 Behavior
Implicit Implicit Explicit Explicitvelocity_limit effort_limit velocity_limit effort_limitIgnored, not set into simulation Set into simulation Used by actuator models (e.g., DC Motor), not set into simulation Used by actuator models, not set into simulationSet into simulation Set into simulation Used by actuator models (e.g., DC Motor), set into simulation Used by actuator models, set into simulation

Setting the limits from the configuration into the simulation directly affects the behavior of the underlying physics engine solver. This impact is particularly noticeable when velocity limits are too restrictive, especially in joints with high stiffness, where it becomes easier to reach these limits. As a result, the change in behavior caused previously trained policies to not function correctly in IsaacLab v2.0.1.

Consequently, we have reverted back to the prior behavior and added velocity_limit_sim and effort_limit_sim attributes to make it clear that setting those parameters means changing solver’s configuration. The new behavior is as follows:

AttributeImplicit ActuatorExplicit Actuator
velocity_limit effort_limit velocity_limit_sim effort_limit_simIgnored, not set into simulation Set into simulation (same as effort_limit_sim) Set into simulation Set into simulation (same as effort_limit)Used by the model (e.g., DC Motor), not set into simulation Used by the models, not set into simulation Set into simulation Set into simulation

Users are advised to use the xxx_sim flag if they want to directly modify the solver limits.

Removal of disable_contact_processing flag in SimulationCfg

Removal of disable_contact_processing flag in SimulationCfg

We have now removed the disable_contact_processing flag from the isaaclab.sim.SimulationCfg to not have the user worry about these intricacies of the simulator. The flag is always True by default unless a contact sensor is created (which will internally set this flag to False).

Previously, the flag disable_contact_processing led to confusion about its behavior. As the name suggests, the flag controls the contact reporting from the underlying physics engine, PhysX. Disabling this flag (note the double negation) means that PhysX collects the contact information from its solver and allows reporting them to the user. Enabling this flag means this operation is not performed and the overhead of it is avoided.

Many of our examples (for instance, the locomotion environments) were setting this flag to True which meant the contacts should not get reported. However, this issue was not noticed earlier since GPU simulation bypasses this flag, and only CPU simulation gets affected. Running the same examples on CPU device led to different behaviors because of this reason.

Existing users, who currently set this flag themselves, should receive a deprecated warning mentioning the removal of this flag and the switch to the new default behavior.

Switch to older rendering settings to improve render quality

With the IsaacLab 2.0.0 release, we switched to new render settings aimed at improving tiled-rendering performance, but at the cost of reduced rendering quality. This change particularly affected dome lighting in the scene, which is the default in many of our examples.

As reported by several users, this change negatively impacted render quality, even in cases where it wasn’t necessary (such as when recording videos of the simulation). In response to this feedback, we have reverted to the previous render settings by default to restore the quality users expected.

For users looking to trade render quality for speed, we will provide guidelines in the future.

v2.0.1

Overview

This release contains a small set of fixes and improvements.

The main change was to maintain combability with the updated library name for RSL RL, which breaks the previous installation methods for Isaac Lab. This release provides the necessary fixes and updates in Isaac Lab to accommodate for the name change and maintain combability with installation for RSL RL.

Full Changelog: https://github.com/isaac-sim/IsaacLab/compare/v2.0.0…v2.0.1

Improvements

Bug Fixes

New Contributors

v2.0.0

Overview

Isaac Lab 2.0 brings some exciting new features, including a new addition to the Imitation Learning workflow with the Isaac Lab Mimic extension.

Isaac Lab Mimic provides the ability to automatically generate additional trajectories based on just a few human collected demonstrations, allowing for larger training datasets with less human effort. This work is based on the MimicGen work for Scalable Robot Learning using Human Demonstrations.

Additionally, we introduced a new set of AMP tasks based on Adversarial Motion Priors, training humanoid robots to walk, run, and dance.

Along with Isaac Lab 2.0, Isaac Sim 4.5 brings several new and breaking changes, including a full refactor of the Isaac Sim extensions, an improved URDF importer, an update to the PyTorch dependency to version 2.5.1, and many fixes for tiled rendering that now supports multiple tiled cameras at different resolutions.

To follow the refactoring in Isaac Sim, we made similar refactoring and restructuring changes to Isaac Lab. These breaking changes will no longer be compatible with previous Isaac Sim versions.

Please make sure to update to Isaac Sim 4.5 when using the Isaac Lab 2.0 release.

Full Changelog: https://github.com/isaac-sim/IsaacLab/compare/v1.4.1…v2.0.0

Highlights from the Isaac Sim 4.5 release

  • Support for multiple TiledCamera instances and varying resolutions
  • Improved rendering performance by up to 1.2x
  • Faster startup time through optimizations in the Cloner class that improves startup time by 30%
  • Enhanced OmniPVD for debugging physics simulation, enabling capturing reinforcement learning simulation
  • Physics simulation performance optimizations improving throughput of up to 70%
  • Physics support for dedicated cylinder and cone geometry designed for robot wheels that is fully GPU accelerated
  • A new physics GPU filtering mechanism allowing co-location of reinforcement learning environments at the origin with minimal performance loss for scenes with limited collider counts
  • Improvements in simulation stability for mimic joints at high joint gains

New Features

  • Adds humanoid AMP tasks for direct workflow by @Toni-SM
  • Adds Isaac Lab Mimic based on MimicGen data generation for Imitation Learning by @peterd-NV @nvcyc @ashwinvkNV @karsten-nvidia
  • Adds consolidated demo script for showcasing recording and mimic dataset generation in real-time in one simulation script by @nvcyc
  • Adds Franka stacking environment for GR00T mimic by @peterd-NV @nvcyc
  • Adds option to filter collisions and real-time playback by @kellyguo11

Improvements

  • Adds a tutorial for policy inference in a prebuilt USD scene by @oahmednv
  • Adds unit tests for multi-tiled cameras by @matthewtrepte
  • Updates render setting defaults for better quality by @kellyguo11
  • Adds a flag to wait for texture loading completion when reset by @oahmednv
  • Adds pre-trained checkpoints and tools for generating and uploading checkpoints by @nv-cupright
  • Adds new denoiser optimization flags for rendering by @kellyguo11
  • Updates torch to 2.5.1 by @kellyguo11

Bug Fixes

  • Fixes external force buffers to set to zero when no forces/torques are applied by @matthewtrepte
  • Fixes RSL-RL package name in setup.py according to PyPI installation by @samibouziri

Breaking Changes

  • Updates the URDF and MJCF importers for Isaac Sim 4.5 by @Dhoeller19
  • Renames Isaac Lab extensions and folders by @kellyguo11
  • Restructures extension folders and removes old imitation learning scripts by @kellyguo11
  • Renames default conda and venv Python environment from isaaclab to env_isaaclab by @Toni-SM

We have identified a breaking feature for semantic segmentation and instance segmentation when using TiledCamera with instanceable assets. Since the Isaac Sim 4.5 / Isaac Lab 2.0 release, semantic and instance segmentation outputs only render the first tile correctly and produces blank outputs for the remaining tiles. We will be introducing a workaround for this fix to remove scene instancing if semantic segmentation or instance segmentation is required for TiledCamera until we receive a proper fix from Omniverse as part of the next Isaac Sim release.

Migration Guide

Renaming of Isaac Sim Extensions

Previously, Isaac Sim extensions have been following the convention of omni.isaac.*, such as omni.isaac.core. In Isaac Sim 4.5, Isaac Sim extensions have been renamed to use the prefix isaacsim, replacing omni.isaac. In addition, many extensions have been renamed and split into multiple extensions to prepare for a more modular framework that can be customized by users through the use of app templates.

Notably, the following commonly used Isaac Sim extensions in Isaac Lab are renamed as follow:

  • omni.isaac.cloner —> isaacsim.core.cloner
  • omni.isaac.core.prims —> isaacsim.core.prims
  • omni.isaac.core.simulation_context —> isaacsim.core.api.simulation_context
  • omni.isaac.core.utils —> isaacsim.core.utils
  • omni.isaac.core.world —> isaacsim.core.api.world
  • omni.isaac.kit.SimulationApp —> isaacsim.SimulationApp
  • omni.isaac.ui —> isaacsim.gui.components

Renaming of the URDF and MJCF Importers

Starting from Isaac Sim 4.5, the URDF and MJCF importers have been renamed to be more consistent with the other extensions in Isaac Sim. The importers are available on isaac-sim GitHub as open source projects.

Due to the extension name change, the Python module names have also been changed:

  • URDF Importer: isaacsim.asset.importer.urdf (previously omni.importer.urdf)
  • MJCF Importer: isaacsim.asset.importer.mjcf (previously omni.importer.mjcf)

From the Isaac Sim UI, both URDF and MJCF importers can now be accessed directly from the File > Import menu when selecting a corresponding .urdf or .xml file in the file browser.

Changes in URDF Importer

Isaac Sim 4.5 brings some updates to the URDF Importer, with a fresh UI to allow for better configurations when importing robots from URDF. As a result, the Isaac Lab URDF Converter has also been updated to reflect these changes. The isaaclab.sim.converters.UrdfConverterCfg includes some new settings, such as ~isaaclab.sim.converters.JointDriveCfg.PDGainsCfg and ~isaaclab.sim.converters.JointDriveCfg.NaturalFrequencyGainsCfg classes for configuring the gains of the drives.

One breaking change to note is that the isaaclab.sim.converters.UrdfConverterCfg.JointDriveCfg.gains attribute must be of class type ~isaaclab.sim.converters.JointDriveCfg.PDGainsCfg or ~isaaclab.sim.converters.JointDriveCfg.NaturalFrequencyGainsCfg.

The stiffness of the ~isaaclab.sim.converters.JointDriveCfg.PDGainsCfg must be specified, as such:

joint_drive=sim_utils.UrdfConverterCfg.JointDriveCfg(
    gains=sim_utils.UrdfConverterCfg.JointDriveCfg.PDGainsCfg(stiffness=None, damping=None)
)

The isaaclab.sim.converters.JointDriveCfg.NaturalFrequencyGainsCfg.natural_frequency attribute must be specified for ~isaaclab.sim.converters.JointDriveCfg.NaturalFrequencyGainsCfg.

Renaming of Isaac Lab Extensions and Folders

Corresponding to Isaac Sim 4.5 changes, we have also made some updates to the Isaac Lab directories and extensions. All extensions that were previously under source/extensions are now under the source/ directory directly. The source/apps and source/standalone folders have been moved to the root directory and are now called apps/ and scripts/.

Isaac Lab extensions have been renamed to:

  • omni.isaac.lab —> isaaclab
  • omni.isaac.lab_assets —> isaaclab_assets
  • omni.isaac.lab_tasks —> isaaclab_tasks

In addition, we have split up the previous source/standalone/workflows directory into scripts/imitation_learning and scripts/reinforcement_learning directories. The RSL RL, Stable-Baselines, RL_Games, SKRL, and Ray directories are under scripts/reinforcement_learning, while Robomimic and the new Isaac Lab Mimic directories are under scripts/imitation_learning.

To assist with the renaming of Isaac Lab extensions in your project, we have provided a simple script that will traverse through the source and docs directories in your local Isaac Lab project and replace any instance of the renamed directories and imports. Please use the script at your own risk as it will overwrite source files directly.

Restructuring of Isaac Lab Extensions

With the introduction of isaaclab_mimic, designed for supporting data generation workflows for imitation learning, we have also split out the previous wrappers folder under isaaclab_tasks to its own module, named isaaclab_rl. This new extension will contain reinforcement learning specific wrappers for the various RL libraries supported by Isaac Lab.

The new isaaclab_mimic extension will also replace the previous imitation learning scripts under the robomimic folder. We have removed the old scripts for data collection and dataset preparation in favor of the new mimic workflow. For users who prefer to use the previous scripts, they will be available in previous release branches.

Additionally, we have also restructured the isaaclab_assets extension to be split into robots and sensors subdirectories. This allows for clearer separation between the pre-defined configurations provided in the extension.

As an example, the following import:

from omni.isaac.lab_assets.anymal import ANYMAL_C_CFG

should be replaced with:

from isaaclab_assets.robots.anymal import ANYMAL_C_CFG

v1.4.1

Overview

This release contains a set of improvements and bug fixes.

Most importantly, we reverted one of the changes from the previous release to ensure the training throughput performance remains the same.

Full Changelog: https://github.com/isaac-sim/IsaacLab/compare/v1.4.0…v1.4.1

This is the final release compatible with Isaac Sim 4.2. The next release will target Isaac Sim 4.5, which introduces breaking changes that will make Isaac Lab incompatible with earlier versions of Isaac Sim.

New Features

Improvements

Bug Fixes

New Contributors

v1.4.0

Overview

Due to a great amount of amazing updates, we are putting out one more Isaac Lab release based off of Isaac Sim 4.2. This release contains many great new additions and bug fixes, including several new environments, distributed training and hyperparameter support with Ray, new live plot feature for Manager-based environments, and more.

We will now spend more focus on the next Isaac Lab release geared towards the new Isaac Sim 4.5 release coming soon. The upcoming release will contain breaking changes in both Isaac Lab and Isaac Sim and breaks backwards compatibility, but will come with many great fixes and improvements.

Full Changelog: https://github.com/isaac-sim/IsaacLab/compare/v1.3.0…v1.4.0

New Features

Improvements

Bug Fixes

Breaking Changes

New Contributors

v1.3.0

Overview

This release will be a final release based on Isaac Sim 4.2 before the transition to Isaac Sim 4.5, which will likely contain breaking changes and no longer backwards compatible with Isaac Sim 4.2 and earlier. In this release, we introduce many features, improvements, and bug fixes, including IMU sensors, support for various types of gymnasium spaces, manager-based perception environments, and more.

Full Changelog: https://github.com/isaac-sim/IsaacLab/compare/v1.2.0…v1.3.0

New Features

Improvements

Bug Fixes

New Contributors

v1.2.0

Overview

We leverage the new release of Isaac Sim, 4.2.0, and bring RTX-based tiled rendering, support for multi-agent environments, and introduce many bug fixes and improvements.

Additionally, we have published an example for generating rewards using an LLM based on Eureka, available here: https://github.com/isaac-sim/IsaacLabEureka

Full Changelog: https://github.com/isaac-sim/IsaacLab/compare/v1.1.0…v1.2.0

New Features

Improvements

Bug Fixes

Breaking Changes

Migration Guide

Setting the simulation device into the simulation context

Previously, changing the simulation device to CPU required users to set other simulation parameters (such as disabling GPU physics and GPU pipelines). This made setting up the device appear complex. We now simplify the checks for device directly inside the simulation context, so users only need to specify the device through the configuration object.

Before:

sim_utils.SimulationCfg(device="cpu", use_gpu_pipeline=False, dt=0.01, physx=sim_utils.PhysxCfg(use_gpu=False))

Now:

sim_utils.SimulationCfg(device="cpu", dt=0.01, physx=sim_utils.PhysxCfg())

Setting the simulation device from CLI

Previously, users could specify the device through the command line argument --device_id. However, this made it ambiguous when users wanted to set the device to CPU. Thus, instead of the device ID, users need to specify the device explicitly through the argument --device. The valid options for the device name are:

  • “cpu”: runs simulation on CPU
  • “cuda”: runs simulation on GPU with device ID at default index
  • “cuda:N”: runs simulation on GPU with device ID at N. For instance, “cuda:0” will use device at index “0”.

Due to the above change, the command line interaction with some of the scripts has changed.

Before:

./isaaclab.sh -p source/standalone/workflows/sb3/train.py --task Isaac-Cartpole-v0 --headless --cpu

Now:

./isaaclab.sh -p source/standalone/workflows/sb3/train.py --task Isaac-Cartpole-v0 --headless --device cpu

Renaming of teleoperation device CLI in standalone scripts

Since --device is now an argument provided by the AppLauncher, it conflicted with the command-line argument used for specifying the teleoperation-device in some of the standalone scripts. Thus, to fix this conflict, the teleoperation-device now needs to be specified through --teleop_device argument.

Before:

./isaaclab.sh -p source/standalone/environments/teleoperation/teleop_se3_agent.py --task Isaac-Lift-Cube-Franka-IK-Rel-v0 --num_envs 1 --device keyboard

Now:

./isaaclab.sh -p source/standalone/environments/teleoperation/teleop_se3_agent.py --task Isaac-Lift-Cube-Franka-IK-Rel-v0 --num_envs 1 --teleop_device keyboard

Using Python-version of container utility script

The prior container.sh became quite complex as it had many different use cases in one script. For instance, building a docker image for “base” or “ros2”, as well as cluster deployment. As more users wanted to have the flexibility to overlay their own docker settings, maintaining this bash script became cumbersome. Hence, we migrated its features into a Python script in this release. Additionally, we split the cluster-related utilities into their own script inside the docker/cluster directory.

We still maintain backward compatibility for container.sh. Internally, it calls the Python script container.py. We request users to use the Python script directly.

Before:

./docker/container.sh start

Now:

./docker/container.py start

Using separate directories for logging videos in RL workflows

Previously, users could record videos during the RL training by specifying the --video flag to the train.py script. The videos would be saved inside the videos directory in the corresponding log directory of the run.

Since many users requested to also be able to record videos while inferencing the policy, recording videos have also been added to the play.py script. Since changing the prefix of the video file names is not possible, the videos from the train and play scripts are saved inside the videos/train and videos/play directories, respectively.

Drops support for the tiled camera with Isaac Sim 4.1

Various fixes have been made to the tiled camera rendering pipeline in Isaac Sim 4.2. This made supporting the tiled camera with Isaac Sim 4.1 difficult. Hence, for the best experience, we advice switching to Isaac Sim 4.2 with this release of Isaac Lab.

New Contributors

v1.1.0

Overview

With the release of Isaac Sim 4.0 and 4.1, support for Isaac Sim 2023.1.1 has been discontinued. We strongly encourage all users to upgrade to Isaac Sim 4.1 to take advantage of the latest features and improvements. For detailed information on this upgrade, please refer to the release notes available here.

Besides the above, the Isaac Lab release brings new features and improvements, as detailed below. We thank all our contributors for their continued support.

Full Changelog: https://github.com/isaac-sim/IsaacLab/compare/v1.0.0…v1.1.0

New Features

Improvements

Bug Fixes

Breaking Changes

Migration Guide

Renaming of SimulationCfg.substeps

Renaming of SimulationCfg.substeps

Previously, the users set both omni.isaac.lab.sim.SimulationCfg.dt and omni.isaac.lab.sim.SimulationCfg.substeps, which marked the physics insulation time-step and sub-steps, respectively. It was unclear whether sub-steps meant the number of integration steps inside the physics time-step dt or the number of physics steps inside a rendering step.

Since in the code base, the attribute was used as the latter, it has been renamed to render_interval for clarity.

Removal of Deprecated Attributes

As notified in previous releases, we removed the classes and attributes marked as deprecated. These are as follows:

  • The mdp.add_body_mass method in the events. Please use the mdp.randomize_rigid_body_mass instead.

  • The classes managers.RandomizationManager and managers.RandomizationTermCfg. Please use the managers.EventManager and managers.EventTermCfg classes instead.

  • The following properties in omni.isaac.lab.sensors.FrameTransformerData:

    • target_rot_source —> target_quat_w
    • target_rot_w —> target_quat_source
    • source_rot_w —> source_quat_w

  • The attribute body_physx_view from the omni.isaac.lab.assets.Articulation and omni.isaac.lab.assets.RigidObject classes. These caused confusion when used with the articulation view since the body names did not follow the same ordering.

v1.0.0

Overview

Welcome to the first official release of Isaac Lab!

Building upon the foundation of the Orbit framework, we have integrated the RL environment designing workflow from OmniIsaacGymEnvs. This allows users to choose a suitable task-design approach for their applications.

While we maintain backward compatibility with Isaac Sim 2023.1.1, we highly recommend using Isaac Lab with Isaac Sim 4.0.0 version for the latest features and improvements.

Full Changelog: https://github.com/isaac-sim/IsaacLab/compare/v0.3.1…v1.0.0

New Features

  • Integrated CI/CD pipeline, which is triggered on pull requests and publishes the results publicly
  • Extended support for Windows OS platforms
  • Added tiled rendered based Camera sensor implementation. This provides optimized RGB-D rendering throughputs of up to 10k frames per second.
  • Added support for multi-GPU and multi-node training for the RL-Games library
  • Integrated APIs for environment designing (direct workflow) without relying on managers
  • Added implementation of delayed PD actuator model
  • Added various new learning environments:
    • Cartpole balancing using images
    • Shadow hand cube reorientation
    • Boston Dynamics Spot locomotion
    • Unitree H1 and G1 locomotion
    • ANYmal-C navigation
    • Quadcopter target reaching

Improvements

  • Reduced start-up time for scripts (inherited from Isaac Sim 4.0 improvements)
  • Added lazy buffer implementation for rigid object and articulation data. Instead of updating all the quantities at every step call, the lazy buffers are updated only when the user queries them
  • Added SKRL support to more environments

Breaking Changes

For users coming from Orbit, this release brings certain breaking changes. Please check the migration guide for more information.

Migration Guide

Please find detailed migration guides as follows:

New Contributors