Create How-To-SLAM-With-Veloview.md

Guide on yet-to-be-released SLAM feature.

Documentation/How-To-SLAM-With-Veloview.md

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+A quick summary to install Veloview on Windows 10 based on Veloview’s [Developer Guide](https://github.com/Kitware/VeloView/blob/master/Documentation/VeloView_Developer_Guide.md#superbuild-overview) and Pierre Guilbert's help in [Issue #51](https://github.com/Kitware/VeloView/issues/51). Note that the newer Veloview with pcl and ceres features must be installed.
+
+# Installing Veloview
+
+## Veloview with SLAM on Windows 10
+1. Follow Veloview's [Developer Guide](https://github.com/Kitware/VeloView/blob/master/Documentation/VeloView_Developer_Guide.md#superbuild-overview) instructions to build Veloview in Windows, and stop at step #5. For Step #6, a different command that enables pcl and ceres for SLAM features will need to be used.
+
+2. Use this cmake command instead of the one in step #6 of the Devloper's Guide so that superbuild will download pcl and ceres sources will be downloaded and compiled:
+    ```
+    cmake C:\Veloview-source\Superbuild -GNinja -DCMAKE_BUILD_TYPE=Release -DUSE_SYSTEM_qt5=True -DQt5_DIR="C:/Qt/Qt5.10.0/5.10.0/msvc2015_64/lib/cmake/Qt5" -DENABLE_pcl=True -DENABLE_ceres=True
+     ```
+
+3. To start building, type `ninja` in the command line. When build is complete, the Veloview.exe application can be found in `<work-directory>\VeloView-build\install\bin`. 
+
+4. Enable pcl and ceres now that you have pcl and ceres files in build folder:
+   - Open a VS2015 cmd terminal and change directory to `${PATH_TO_BUILD}\common-superbuild\veloview\build`
+   - Open cmake-gui by typing `cmake-gui . `, including the fullstop ".".
+   - Enable options ENABLE_pcl and ENABLE_ceres by clicking the tickboxes
+   - Click 'Generate' to create relevant new files
+   - Close cmake-gui, recompile Veloview again by typing `ninja install` in the same location.
+
+Veloview with SLAM on Linux coming soon.
+(I just need to sit down and organize all the info!)
+
+
+- - - - - - - - - - - - - - - - - - - 
+
+
+# Using SLAM in Veloview
+See [Veloview's SLAM Presentation](https://github.com/etanx/VeloView/blob/master/Documentation/slam_presentation.docx) for more info about Veloview's SLAM algorithm. Note: SLAM has been tested with .pcap files from the VLP-32c.
+
+Open Veloview. Make sure Advanced Features are enabled.
+
+![exportformat](https://user-images.githubusercontent.com/22595013/60025272-9544fd80-9699-11e9-8901-e12dc0662b3d.png)
+
+Enable Pipeline Browser and Properties under ‘Views’ tab. 
+
+![exportformat](https://user-images.githubusercontent.com/22595013/60025310-a857cd80-9699-11e9-848e-f147fcee74f9.png)
+
+Open a .pcap file (or sensor stream) from the LIDAR folder on Desktop
+
+In Pipeline browser, select Calibration (the source), click on Filters tab and search for ‘SLAM’. 
+
+![exportformat](https://user-images.githubusercontent.com/22595013/56412530-d1687600-6284-11e9-9ec0-8731ff9f9ab6.png)
+
+Hit ‘Enter’ to select a SLAM filter: Pick *Slam (online)* to see it do a test live display (not as accurate since it skips some frames), or *SLAM (offline)* for a full process.
+
+A new input dialog will appear. 
+
+![exportformat](https://user-images.githubusercontent.com/22595013/56412718-64091500-6285-11e9-9de3-10b8f17e1434.png)
+
+Click the Point Cloud input port, select the ‘Frame’ green cube. 
+Click the Calibration input port, select the ‘Calibration’ entry. 
+Hit ‘Ok’ when done.
+
+Under properties, hit ‘Apply’ after you’re done searching and changing algorithm properties (default ones are good to start with).
+- If you chose online SLAM, a white frame will appear. Hit playback to play through the entire recording and watch it SLAM.
+- If you chose offline SLAM, nothing will happen after you hit ‘Apply’, but that’s okay, the computer is working hard to SLAM stuff.
+
+Once SLAM is complete, you can export the Trajectory as .poses to avoid running the SLAM again (selecting the Trajectory and ctrl + s). Then, to load the trajectory you can drag and drop the .poses file.
+
+# Exporting Pointclouds
+To export all frames processed, you need to instanciate a "Transforms Applier" and processes the pointcloud geenerator (data) and the trajectory (sensor path estimated by SLAM):
+- Select the trailing frame and set the desired number of trailing frames (it will display the frames [|current_frame - Ntrailingframe, current_frame|]). 
+- Click on apply. You should now see all the frames aggregated in a non-sense way (all points being displayed using their coordinates of the reference frame attached to the sensor at the time of acquisition).
+- Instantiate a "Transform Applier" with point cloud <-> the output of the Extract Surface and trajectory <-> the one estimated by the SLAM.
+
+
+Save/Export the complete pointcloud for further processing.
+
+
+
+Note: The default SLAM parameters are a good compromise to make the SLAM working in outdoor urban area, indoor scene and poor geometric scene (forest recorded from UAV, glades, career, ...).
+However, the parameters can be adapted to the specific kind of environment you want to process to have an optimal result.
+