Glossary: SLAM - Simultaneous Localization and Mapping

Simultaneous Localization and Mapping (SLAM) is a robotics technique that allows a robot to create a map of an unfamiliar environment while simultaneously determining its own position within that map.

SLAM is particularly important for autonomous mobile robots (AMRs) because a robot needs to understand both where it is and what its environment looks like to effectively navigate.

SLAM systems can combine data from technologies such as LiDAR, cameras, inertial measurement units (IMUs), wheel encoders and other sensors. The resulting map can support navigation, obstacle avoidance, localization and path planning.

SLAM is often associated as a foundational technology behind many AMRs and other robotic navigation systems.

Related terms: AMR, LiDAR, Sensor Fusion, Path Planning, Computer Vision