The Definitive Guide to SLAM & Mobile Mapping

The Definitive Guide to SLAM & Mobile Mapping

What is simultaneous localization and mapping? How does it affect the accuracy of your scan data? Why do some SLAM systems process data faster than others? Presenting the definitive guide to SLAM from NavVis, where all your questions will be answered. It includes virtually every piece of information you could need to understand the ins and outs of this fascinating technology.

Simultaneous localization and mapping (SLAM) is not a specific software application, or even one single algorithm. SLAM is a broad term for a technological process, developed in the 1980s, that enabled robots to navigate autonomously through new environments without a map.

Autonomous navigation requires locating the machine in the environment while simultaneously generating a map of that environment. It’s very difficult to accomplish, because the machine needs to have a map of the environment to estimate its own location. But to generate the map, it needs to know its own location.

Due to the rapid growth of computing power since the 1980s – not to mention the availability of freely downloadable code from companies like Google – SLAM is now used in a wide variety of applications. In fact, you’ll see it in virtually every application where a machine requires a live 3D map of its surroundings to operate.

Now we can talk about the application of SLAM most important to us: mobile mapping systems. You can think of these tools as laser scanners designed to offer the best possible building documentation workflows.

Mobile mapping systems use a combination of highly calibrated sensors and SLAM technology optimized for mapping. These tools enable you to capture 3D point clouds and panoramic images as you walk. They offer fast, comprehensive documentation for large assets and complex environments like factories work sites, and offices.

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