Best approach to mapping interior point cloud with LIDAR

Question

Recently started playing with and built a 3D LIDAR using an Arduino, 2 servos and a Garmin Lite 3 LIDAR. Stationary mapping works great, but now I would like to move into interior mapping with a handheld unit. With an exterior unit I would of course rely on GPS, but what is the best approach for obtaining a decent interior point cloud?

I could of course rely on additional sensors to "map" the movement of the unit—but I would assume that the result would not be that great—or, and this solution I personally would have a harder time implementing, plot points based off of the the change of existing plot (ie the unit identifies that it is moving away from a corner of the room).

Any tips, example, etc. would be appreciated. Cheers!

Answer 1

Indoor mobile mapping is often done with Simultaneous Localization And Mapping (SLAM) . SLAM algorithms and their implementations is an area of active research; one project to check out is OpenSLAM . They provide source code that could be used to build your own SLAM solution, and their paper (pdf) includes more background and the results of some real-world tests.

In terms of additional hardware you will need, an Inertial Measurement Unit (IMU) provides information about the attitude and acceleration of your system. These are more-or-less a requirement for all mobile systems, whether in a GNSS-denied environment or not.

Good luck!