The same core idea, wildly different scales
Robot vacuums from companies like iRobot use visual or LiDAR-based SLAM to map a home over the first few cleaning cycles, then reuse that map on subsequent runs while still correcting for small changes, like furniture that moved. It's SLAM at a small, forgiving scale: low speed, small area, low consequence if a position estimate is briefly a few centimeters off.
Warehouse autonomous mobile robots, from companies like Locus Robotics and Amazon's warehouse robotics fleets, run SLAM and navigation continuously across much larger, busier spaces shared with human workers and other robots, where accurate localization directly affects throughput and safety. These systems typically combine SLAM with pre-built facility maps, using live sensing to localize precisely within a known layout rather than building the entire map fresh from nothing every run.