SLAM

What is SLAM?

Simultaneous Localization and Mapping

Simultaneous Localization and Mapping (SLAM) refers to the computational process where a device creates a map of its surroundings while simultaneously tracking its position within that environment, essential for spatial understanding in AR applications.

How does SLAM work?

SLAM (Simultaneous Localization and Mapping) enables devices to build three-dimensional representations of unknown environments while tracking their own movement through that space, solving the interdependent problems of mapping and localization concurrently.

SLAM systems typically combine data from multiple sensors including cameras (visual SLAM), depth sensors, inertial measurement units, and sometimes lidar to create accurate environmental models despite sensor noise and environmental ambiguities. The resulting spatial understanding provides the foundation for advanced AR experiences where virtual content can be anchored precisely to physical locations, remain stable as users move, and interact meaningfully with real-world structures through occlusion, collision, and lighting integration.

How is SLAM used?

Beyond AR, SLAM technologies drive innovations in autonomous navigation, robotics, and spatial computing across industries from manufacturing to healthcare.