Exwayz Merge Cloud aims at accumulating LiDAR frames output by Exwayz SLAM on a trajectory produced by exwayz_slam.exe, exwayz_loop_closure.exe or exwayz_georef.exe to create a dense point cloud. While merging, it can perform basic filetring operations such as using a range filter on each frame or a class filter if classification is available in the frames.
<aside> 💡 Check the 6. Merge frames into a dense point cloud tutorial to learn easily how to run the SLAM.
</aside>
| Name | Command line prefix | Default value | Definition |
|---|---|---|---|
| Frames | -i |
Required | Path to directory containing frames of the SLAM session |
| Trajectory | -t |
Required | Path to the trajectory on which accumulation will be done |
| Output path | -o |
./merged.ply | Name of the output file. Note that specifying the extension in the name will define in which format the point cloud will be written (default is .ply, but it can be .las or .laz). |
| Begin index | --begin |
- | If set, the accumulation is performed only on trajectory points with index greater than --begin |
| End index | --end |
- | If set, the accumulation ends on trajectory points with index greater than --end |
| Help | -h |
- | Prints help message |
| Distance update | -d |
- | Minimal distance between consecutive accumulated frames. It allows to manage the density (and thus, weight) of the overall point cloud |
|---|---|---|---|
| Minimum range | --r-min |
- | Discards, in each frame, all points with a range lesser than --r-min. It is useful to rvemove points that appear on each frame consistenly such as points belonging to the sensor’s mounting platform. |
| Maximum range | --r-max |
- | Discards, in each frame, all points with a range greater than --r-max. It is useful to remove noisy points that measured too far away from the sensor, that can destabilize the SLAM |
| Crop | --crop |
- | If set, this option enable to crop a constant part of each frame, specified in a .yaml configuration file. A box can be specified as a set of minimum and maximum coordinates in (x, y, z), or as a center and sizes in the 3 directions. Boxes are axis-aligned with the each LiDAR frame. An example of configuration file is provided in the <exwayz_install_dir>/example/crop.yaml file. |
| Trajectory sampling | --traj-subsampling |
- | Subsample the trajectory with a Poisson disk strategy (spacing all trajectory points by the value of --traj-subsampling ). This can be useful for assembling coarsly the point cloud and avoid adding redundant info on areas visited a lot. |
| Split the merged point cloud | --split |
- | Allows te software to split the merged point cloud into chunks of ~--split millions of points. This option helps preventing exceeding the total RAM capacity of the computer during the merging step. |
| Keep semantic classes | --cls-keep |
- | Keep points having a given class id (see ‣ for checking the available classes). Possible inputs are among {dynamic, static, ground, cars, trucks, vegetation}. |
| Remove semantic classes | --cls-remove |
- | Remove points having a given class id (see ‣ for checking the available classes). Possible inputs are among {dynamic, static, ground, cars, trucks, vegetation}. |
Exwayz Merge Cloud outputs the merged point cloud in the specified -o file.