Loop Closure

Detecting when the robot has returned to a previously visited location, enabling correction of accumulated drift in SLAM. Loop closure detection uses place recognition (visual bag-of-words, learned descriptors, LiDAR scan matching) to identify revisited locations, then triggers a graph optimization that corrects the entire trajectory. Without loop closure, maps progressively distort with distance traveled.