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=============
.. currentmodule:: isaaclab
Isaac Lab offers several lightweight visualizers for real-time simulation inspection and debugging. Unlike renderers that process sensor data, visualizers are meant for fast, interactive feedback.
You can use any visualizer regardless of your chosen physics engine or rendering backend.
Overview
--------
Isaac Lab supports three visualizer backends, each optimized for different use cases:
.. list-table:: Visualizer Comparison
:widths: 15 35 50
:header-rows: 1
* - Visualizer
- Best For
- Key Features
* - **Omniverse**
- High-fidelity, Isaac Sim integration
- USD, visual markers, live plots
* - **Newton**
- Fast iteration
- Low overhead, visual markers
* - **Rerun**
- Remote viewing, replay
- Webviewer, time scrubbing, recording export
*The following visualizers are shown training the Isaac-Velocity-Flat-Anymal-D-v0 environment.*
.. figure:: ../../_static/visualizers/ov_viz.jpg
:width: 100%
:alt: Omniverse Visualizer
Omniverse Visualizer
.. figure:: ../../_static/visualizers/newton_viz.jpg
:width: 100%
:alt: Newton Visualizer
Newton Visualizer
.. figure:: ../../_static/visualizers/rerun_viz.jpg
:width: 100%
:alt: Rerun Visualizer
Rerun Visualizer
Quick Start
-----------
Launch visualizers from the command line with ``--visualizer``:
.. code-block:: bash
# Launch all visualizers
python scripts/reinforcement_learning/rsl_rl/train.py --task Isaac-Cartpole-v0 --visualizer omniverse newton rerun
# Launch just newton visualizer
python scripts/reinforcement_learning/rsl_rl/train.py --task Isaac-Cartpole-v0 --visualizer newton
If ``--headless`` is given, no visualizers will be launched.
.. note::
The ``--headless`` argument may be deprecated in future versions to avoid confusion with the ``--visualizer``
argument. For now, ``--headless`` takes precedence and disables all visualizers.
Configuration
~~~~~~~~~~~~~
Launching visualizers with the command line will use default visualizer configurations. Default configs can be found and edited in ``source/isaaclab/isaaclab/visualizers``.
You can also configure custom visualizers in the code by defining new ``VisualizerCfg`` instances for the ``SimulationCfg``, for example:
.. code-block:: python
from isaaclab.sim import SimulationCfg
from isaaclab.visualizers import NewtonVisualizerCfg, OVVisualizerCfg, RerunVisualizerCfg
sim_cfg = SimulationCfg(
visualizer_cfgs=[
OVVisualizerCfg(
viewport_name="Visualizer Viewport",
create_viewport=True,
dock_position="SAME",
window_width=1280,
window_height=720,
camera_position=(0.0, 0.0, 20.0), # high top down view
camera_target=(0.0, 0.0, 0.0),
),
NewtonVisualizerCfg(
camera_position=(5.0, 5.0, 5.0), # closer quarter view
camera_target=(0.0, 0.0, 0.0),
show_joints=True,
),
RerunVisualizerCfg(
keep_historical_data=True,
keep_scalar_history=True,
record_to_rrd="my_training.rrd",
),
]
)
Visualizer Backends
-------------------
Omniverse Visualizer
~~~~~~~~~~~~~~~~~~~~
**Main Features:**
- Native USD stage integration
- Visualization markers for debugging (arrows, frames, points, etc.)
- Live plots for monitoring training metrics
- Full Isaac Sim rendering capabilities and tooling
**Core Configuration:**
.. code-block:: python
from isaaclab.visualizers import OVVisualizerCfg
visualizer_cfg = OVVisualizerCfg(
# Viewport settings
viewport_name="Visualizer Viewport", # Viewport window name
create_viewport=True, # Create new viewport vs. use existing
dock_position="SAME", # Docking: 'LEFT', 'RIGHT', 'BOTTOM', 'SAME'
window_width=1280, # Viewport width in pixels
window_height=720, # Viewport height in pixels
# Camera settings
camera_position=(8.0, 8.0, 3.0), # Initial camera position (x, y, z)
camera_target=(0.0, 0.0, 0.0), # Camera look-at target
# Feature toggles
enable_markers=True, # Enable visualization markers
enable_live_plots=True, # Enable live plots (auto-expands frames)
)
Newton Visualizer
~~~~~~~~~~~~~~~~~~~~~~~~~
**Main Features:**
- Lightweight OpenGL rendering with low overhead
- Visualization markers (joints, contacts, springs, COM)
- Training and rendering pause controls
- Adjustable update frequency for performance tuning
- Some customizable rendering options (shadows, sky, wireframe)
**Interactive Controls:**
.. list-table::
:widths: 30 70
:header-rows: 1
* - Key/Input
- Action
* - **W, A, S, D** or **Arrow Keys**
- Forward / Left / Back / Right
* - **Q, E**
- Down / Up
* - **Left Click + Drag**
- Look around
* - **Mouse Scroll**
- Zoom in/out
* - **Space**
- Pause/resume rendering (physics continues)
* - **H**
- Toggle UI sidebar
* - **ESC**
- Exit viewer
**Core Configuration:**
.. code-block:: python
from isaaclab.visualizers import NewtonVisualizerCfg
visualizer_cfg = NewtonVisualizerCfg(
# Window settings
window_width=1920, # Window width in pixels
window_height=1080, # Window height in pixels
# Camera settings
camera_position=(8.0, 8.0, 3.0), # Initial camera position (x, y, z)
camera_target=(0.0, 0.0, 0.0), # Camera look-at target
# Performance tuning
update_frequency=1, # Update every N frames (1=every frame)
# Physics debug visualization
show_joints=False, # Show joint visualizations
show_contacts=False, # Show contact points and normals
show_springs=False, # Show spring constraints
show_com=False, # Show center of mass markers
# Rendering options
enable_shadows=True, # Enable shadow rendering
enable_sky=True, # Enable sky rendering
enable_wireframe=False, # Enable wireframe mode
# Color customization
background_color=(0.53, 0.81, 0.92), # Sky/background color (RGB [0,1])
ground_color=(0.18, 0.20, 0.25), # Ground plane color (RGB [0,1])
light_color=(1.0, 1.0, 1.0), # Directional light color (RGB [0,1])
)
Rerun Visualizer
~~~~~~~~~~~~~~~~
**Main Features:**
- Web viewer interface accessible from local or remote browser
- Metadata logging and filtering
- Recording to .rrd files for offline replay (.rrd files can be opened with ctrl+O from the web viewer)
- Timeline scrubbing and playback controls of recordings
**Core Configuration:**
.. code-block:: python
from isaaclab.visualizers import RerunVisualizerCfg
visualizer_cfg = RerunVisualizerCfg(
# Server settings
app_id="isaaclab-simulation", # Application identifier for viewer
web_port=9090, # Port for local web viewer (launched in browser)
# Camera settings
camera_position=(8.0, 8.0, 3.0), # Initial camera position (x, y, z)
camera_target=(0.0, 0.0, 0.0), # Camera look-at target
# History settings
keep_historical_data=False, # Keep transforms for time scrubbing
keep_scalar_history=False, # Keep scalar/plot history
# Recording
record_to_rrd="recording.rrd", # Path to save .rrd file (None = no recording)
)
Performance Note
----------------
To reduce overhead when visualizing large-scale environments, consider:
- Using Newton instead of Omniverse or Rerun
- Reducing window sizes
- Higher update frequencies
- Pausing visualizers while they are not being used
Limitations
-----------
**Rerun Visualizer Performance**
The Rerun web-based visualizer may experience performance issues or crashes when visualizing large-scale
environments. For large-scale simulations, the Newton visualizer is recommended. Alternatively, to reduce load,
the num of environments can be overwritten and decreased using ``--num_envs``:
.. code-block:: bash
python scripts/reinforcement_learning/rsl_rl/train.py --task Isaac-Cartpole-v0 --visualizer rerun --num_envs 512
.. note::
A future feature will support visualizing only a subset of environments, which will improve visualization performance
and reduce resource usage while maintaining full-scale training in the background.
**Rerun Visualizer FPS Control**
The FPS control in the Rerun visualizer UI may not affect the visualization frame rate in all configurations.
**Newton Visualizer Contact and Center of Mass Markers**
Contact and center of mass markers are not yet supported in the Newton visualizer. This will be addressed in a future release.
**Newton Visualizer CUDA/OpenGL Interoperability Warnings**
On some system configurations, the Newton visualizer may display warnings about CUDA/OpenGL interoperability:
.. code-block:: text
Warning: Could not get MSAA config, falling back to non-AA.
Warp CUDA error 999: unknown error (in function wp_cuda_graphics_register_gl_buffer)
Warp UserWarning: Could not register GL buffer since CUDA/OpenGL interoperability
is not available. Falling back to copy operations between the Warp array and the
OpenGL buffer.
The visualizer will still function correctly but may experience reduced performance due to falling back to
CPU copy operations instead of direct GPU memory sharing.
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