All evaluation methodologies
Absolute Trajectory Error
ATE compares the trajectory of a robot, as reconstructed by an algorithm using real sensor data as its input, to the actual trajectory (ground truth). ATE is a mandatory performance measure. Please note that the Rawseeds Metrics Computation Toolkit (downloadable from the page of any data capture s
Mapping Error
ME compares the map of an environment, as reconstructed by an algorithm using real sensor data as its input, to the actual map of the location (ground truth). ME is a recommended performance measure.
Relative Pose Error
RPE measures the accuracy of a SLAM result, as reconstructed by an algorithm using real sensor data as its input, by comparing the reconstructed relative transformations between nearby poses to the actual relative transformations (ground truth). RPE is a recommended performance measure. Please not
Rough Estimate of Complexity
REC provides a basic estimate of how the running time of an algorithm (which uses real sensor data as its input) scales as the quantity of data available to be processed increases. REC is a mandatory performance measure.
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 str