Simulator Addon Guide
Content
- Add-on Description
- Installation
- Add-on functionality
- Generated Outputs
- Contributors
- License
- Acknowledgement
Add-on Description
- Creates a 3D virtual environment of a railway track as a virtual replica of a real track.
- Creates movement of a virtual train respecting user defined conditions.
- Generates various sensory outputs such as RGB image, LIDAR, GPS, thermovision, segmentation map with a ground truth classification, etc.
- Simulates multiple critical scenarios in the virtal environment that might arise on a real track, e.g., collision events, different light and weather conditions (rain, snow, and clouds), etc.
- Generated environment can be populated by static or dynamic objects.
- Outputs from the simulator can be used to develop object detection methods aplicable in the train environment.
Installation
Add-on is compatible with Blender version 3.3 LTS.
For add-on installation you can read Installation and Setup Guide.
Add-on functionality
Basic Usage:
- Go to 3D View Sidebar (N) > Simulator tab.
- In the Create scene panel, select Scenario from the dropdown. Click on Load scenario and then click on Create scene
Scene
Create scene
Manual changes
Hour of the day Hour affects the sky clouds and changes the available clouds in Cloud Type dropdown. |
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Sky selection Cloud Type dropdown can be used to change the cloud type. |
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Objects Add map adds and shrinks selected raster map to terrain to help position added objects.
Advanced assets (i.e. .blend files with advanced keyword in their names) are not allowed to be added to the scene by users. However, those assets may be present in the scene.
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Generated Outputs
Following images show rendered/generated outputs which are saved in out folder: Albedo, Atmosphere, Depth, Glossiness, GPS (.txt), GT, Lidar (.pcd), Normal, RGB and Thermo. out folder is created one folder up where the scene is saved. The node group for generating these render passes can be found in the compositor.
Lidar is created using GT and depth maps. Thermo is a prediction made using a neural network model that is implemented in the PyTorch framework and is based on the Pix2Pix architecture.
GPS output:

Contributors
- Petr Strakos (petr.strakos@vsb.cz)
- Khyati Sethia
- Marta Jaros
- Alena Jesko
- Roman Machacek
- David Ciz
- Alfred Koci
- Vyomkesh Jha
- Ada Bohm
- Petr Jelen
- Tomas Kulich
- Jakub Sipr
License
- This software is licensed under the terms of the GNU General Public License.
- Data in 3D_Assets are proprietary and not freely available. For more information about the possibilities how to acquire them please contact Jakub Sipr (jakub.sipr@ixperta.com) or Petr Strakos (petr.strakos@vsb.cz).
Acknowledgement
Created within the project FW01010274 Research and development of a functional sample of a railway vehicle with the ability to collect data and software - a simulator with the ability to generate data for obstacle detection training in simulated conditions. Co-financed by state support from Technology Agency of the Czech Republic in program TREND.