The ROCK Robotic R1A consists of a LiDAR and an INS. The data gathered from both devices must be fused together to get LiDAR points geo-referenced – transformed from the LiDAR reference frame to geographic coordinates.
The steps for taking the raw data and converting it to a point cloud are as follows:
- Create a highly accurate trajectory
- Use that trajectory to create the point cloud
- (Optional) Colorize the point cloud with imagery.
PCMasterGL works on Windows 10 x64 (MacOS and Linux x64 versions are in development). The key requirement for seamless visualization of large point clouds is a fast GPU with large video memory (dedicated or shared). The software has been tested on nVidia GeForce GTX graphics cards, but it is hardware independent. The rule of thumb is 1 GB of memory for every 15 million points in the cloud. The current software limit is 800 million points. Fast data processing also requires a fast CPU.
Recommended computer specifications:
- Intel Core i7 or better
- 32 GB RAM
- Nvidia GeForce GTX 1050 Ti or better
- Windows 10 x64
Step 1 - Create a highly accurate trajectory