SLAM LiDAR vs GNSS/RTK: Which Do You Need?

Both technologies deliver accurate spatial data, but they solve different problems. Here's the difference, in plain terms.

GNSS/RTK — absolute position, open sky

A GNSS receiver calculates position from satellites, with RTK corrections (see our RTK network guide) for centimeter accuracy. It gives you absolute coordinates in a real geographic reference system, but it needs a clear view of the sky — it doesn't work well indoors, under dense vegetation, or between tall buildings.

SLAM LiDAR — mapping without GNSS

A SLAM (Simultaneous Localization and Mapping) scanner like the Manifold Pocket 2 needs no satellite signal at all. As you walk, the laser scans the environment thousands of times per second, and the algorithm simultaneously works out its own position in space and builds the point cloud. It works just as well indoors, in tunnels, under canopy, or between buildings.

The trade-off

GNSS/RTK gives you absolute georeferencing but needs open sky. SLAM gives you very high-density relative accuracy (the point cloud) with no space constraints, but its accuracy depends on the path itself — over very long, closed loops a small amount of drift can accumulate, though algorithms like the Pocket 2's MindSLAM keep it well controlled.

Combining the two

In practice, many projects use both: known control points measured with GNSS/RTK provide absolute georeferencing, while SLAM LiDAR quickly covers the rest of the space — especially where the GNSS receiver has no signal.

Which one fits your job

• Open sites, surveying, stakeout, cadastral work → GNSS/RTK
• Indoor spaces, tunnels, as-built building surveys, BIM → SLAM LiDAR
• Large, mixed-condition projects → a combination of both

Need centimeter accuracy in open terrain? See our RTK network guide.