Although the onboard processor handles some basic filtering of the incoming LIDAR and position data during scanning, it doesn't have the capacity to generate the point cloud. That is performed using the CAVEATRON PROCESS application. The first step is to generate an X, Y, Z coordinate file from the station survey file. The file can be loaded directly into CAVEATRON PROCESS and the line plot can be viewed and reference stations and global coordinates set. If the survey contains loop closures or multiple surveys are involved, it is highly recommended to use Walls Cave Mapping Software. The survey file can be directly loaded into Walls for processing and a function in Walls generates the necessary X, Y, Z coordinate file to load back into CAVEATRON PROCESS.
The LIDAR data file from the Caveatron is then loaded into the Caveatron Process bringing up a list of the traverses and room scans. Detailed information about each scan is provided. To begin processing, the user selects one of the scans and selects it to Review. This opens the Scan Review window where the scan data can be viewed in details via several plot and each rotation of the scan can be stepped through to view each single cross-section. Outlier points (noisy data) are indicated for removal and the filtering parameters can be adjusted. Another plot shows the rangefinder distance measurements during the scan so that bad data that slipped through the filtering can be selected for removal. A third plot shows a plan or profile section of the scan and provides drop down menus to select the level of processing desired to smooth the data.
Once the scan is reviewed, it is processed to remove LIDAR noise, compute the Caveatron positions between valid measurements, remove excessive motion, compute the normal vector for each point, and then generate the coordinates for each point based on the survey data. The program saves the output as a delimited text file that can then be easily loaded into one of several freely available point-cloud viewing programs such as Cloudcompare or Meshlab. To take the data processing one step further, Meshlab has a function to turn the point cloud into a rendered mesh through a Poisson surface reconstruction algorithm. That creates a 3D file that shows the walls of the cave as a solid surface allowing you to fly around or through the cave on your computer. As a final step, Meshlab can export a file suitable for 3D printing so you can make your own physical cave models!