Robust 3D-Mapping with Time-of-Flight Cameras

Abstract

Time-of-Flight cameras constitute a smart and fast technology for 3D perception but lack in measurement precision and robustness. We present a comprehensive approach for 3D environment mapping based on this technology. Imprecision of depth measurements are properly handled by calibration and application of several filters. Robust registration is performed by a novel extension to the Iterative Closest Point algorithm. Remaining registration errors are reduced by global relaxation after loop-closure and surface smoothing. A laboratory ground truth evaluation is provided as well as 3D mapping experiments in a larger indoor environment.