Visualization ============= .. 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.