SLAM

SLAM (Simultaneous Localization and Mapping) is a computational technique that enables autonomous systems like robots and drones to build a map of an unknown environment while simultaneously tracking their own position within it. It combines sensor data (typically from cameras, LiDAR, or IMUs) with probabilistic algorithms to create real-time spatial awareness without relying on GPS or pre-existing maps.

Companies urgently need SLAM expertise to develop next-generation autonomous vehicles, delivery drones, and augmented reality systems that require precise real-time navigation in dynamic environments. The rapid growth of robotics, warehouse automation, and spatial computing (like Apple Vision Pro) has created intense demand for engineers who can solve the 'where am I?' problem in GPS-denied or complex indoor settings.