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where `$HOME/ws` is an example colcon workspace used to build Gazebo
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where `$HOME/ws` is an example colcon workspace used to build Gazebo.
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On Windows, `gz sim` (i.e. running both server and GUI in one command) doesn't yet work.
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To run Gazebo Sim on Windows, you need to run the server in one terminal (`gz sim -s <other args>`)
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and the GUI in another terminal (`gz sim -g <other args>`). Remember this when reading through
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all Gazebo Sim tutorials. Also remember that Conda and `install\setup.bat` need to be sourced
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in both terminals (as well as any changes to `GZ_PARTITION` and other environment variables).
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# Documentation
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See the [installation tutorial](https://gazebosim.org/api/sim/9/install.html).
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See the [Writing Tests section of the contributor guide](https://github.com/gazebosim/gz-sim/blob/main/CONTRIBUTING.md#writing-tests) for help creating or modifying tests.
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See the [Writing Tests section of the contributor guide](https://gazebosim.org/docs/all/contributing/#writing-tests) for help creating or modifying tests.
Copy file name to clipboardExpand all lines: tutorials/point_cloud_to_mesh.md
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@@ -21,7 +21,7 @@ After installing, open CloudCompare and import your point cloud file by going to
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Depending on the number of points in your point cloud, this could take several minutes.
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Once loaded, you should see the following tunnel section:
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\image html files/point_cloud_to_mesh/cloudcompare2.png
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Many 3D scans will be composed of millions, sometimes hundreds of millions of points.
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Converting a scan to a 3D model with that many points would be very difficult due to the number of polygons that would be created and the long processing time necessary to compute the normals.
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To reduce the number of points in your cloud, click on the tunnel so a yellow cube outline appears around it, then go to `Edit` > `Subsample`.
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\image html files/point_cloud_to_mesh/min_space.jpg
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The number you will need to enter in the `min. space between points` field will vary depending on your point cloud.
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A value of .01 was sufficient to bring our point cloud to an easy-to-manage 1 million points.
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Point count is visible in the `Properties` window on the lower left side of the screen.
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\image html files/point_cloud_to_mesh/properties.png
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How many points you reduce down to will largely depend on how long you are willing to wait for the point cloud to be converted into a mesh.
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The more points you start with, the longer it will take to compute the normals and create the mesh.
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After the operation is complete you’ll have two clouds in your scene: the original point cloud and your subsampled point cloud.
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Most operations in CloudCompare will create new point clouds and keep the original, so make sure that you have the new point cloud selected before running an operation.
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\image html files/point_cloud_to_mesh/secondcloud.png
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### Create a Polygonal Mesh
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\image html files/point_cloud_to_mesh/compute_normals.png
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You’ll see various options in the dialog box that appears.
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The main thing you’ll want to consider is what `Local surface model` to use.
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To do this go to `Plugins` > `PoissonRecon`.
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You'll see this dialog box:
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\image html files/point_cloud_to_mesh/outputdensity.png
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The value you enter in the `Octree depth` field will determine the polygon count of the created model.
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You may have to run the surface reconstruction a couple times with varying values before you land on a polygon count that is suitable for your needs.
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This is because the mesh that CloudCompare creates will always be water tight even if it has to add polygons where there are no points.
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We just want our tunnels, though, so we need to remove those unnecessary polygons.
In the mesh's `Properties` window go to `SF display params` and take the left handle in the graph and drag it to the right until it hits the area where the bulk of the scalar field starts.
\image html files/point_cloud_to_mesh/sf_display.png
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This will display only the polygons that were created from the point cloud and hide the polygons used to make the model watertight.
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The polygons are only hidden however.
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We still need to actually remove them.
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\image html files/point_cloud_to_mesh/hidden_polygons2.jpg
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To remove the hidden polygons go to `Edit` > `Scalar fields` > `Filter By Value`.
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Instead, we'll hit `Split` to create two meshes.
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One with the polygons inside our specified range and one containing polygons outside that range.
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\image html files/point_cloud_to_mesh/split.png
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It is possible that you will get error "Visibility table not instantiated". This error causes only the "wanted" part of the mesh to be created when splitting, while the other ("unwanted") part will not be generated. But that is not a problem for our use-case.
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\image html files/point_cloud_to_mesh/error.jpg
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### The Completed Model
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Before exporting, check your mesh for holes. If still checked, disable display of the pointcloud, so that only your output mesh is shown. Inspect ground parts of the mesh (or any other parts you are most interested in) and check if there aren't holes in it. If there are some, you can try to repeat the trimming step with more relaxed threshold.
\image html files/point_cloud_to_mesh/complete2.png
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You can find more information on CloudCompare and a more in depth look at the tools we used in this tutorial on [the CloudCompare website](https://www.cloudcompare.org/) and the [CloudCompare wiki](https://www.cloudcompare.org/doc/wiki/index.php?title=Main_Page).
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