Self Localization Error
SLE aims to evaluate the overall quality of a SLAM algorithm by actually using its output in a realistic application. The SLAM algorithm, fed with real sensor data from a robot, is used to build a map of the explored environment; then a self-localization algorithm, fed with different sensor data streams collected in the same environment, is used to localize the robot within the map. The precision of such localization is evaluated by comparing it with the actual pose of the robot (ground truth). SLE is a recommended performance measure.