Portable laser range-finders, further referred to as LIDAR, and simultaneous localization and mapping (SLAM) are an efficient method of acquiring as-built floor plans. Generating and visualizing floor plans in real-time helps the operator assess the quality and coverage of capture data. Building a portable capture platform necessitates operating under limited computational resources. We present the approach used in our backpack mapping platform which achieves real-time mapping and loop closure at a 5 cm resolution. To achieve realtime loop closure, we use a branch-and-bound approach for computing scan-to-submap matches as constraints. We provide experimental results and comparisons to other well known approaches which show that, in terms of quality, our approach is competitive with established techniques.

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The following paper presents a model to predict the systematic errors and statistical uncertainties of TOF (Time-of-Flight) 3D-imaging systems. The experimental data obtained with a custom build test setup show that the standard deviation of the depth signal rises approximately quadratically with the depth. The most significant systematic depth error is periodic with an amplitude of around 50 mm. It is provoked by the inharmonic correlation function. The inhomogeneity in each pixel (fixed pattern) accounts for a depth error of about 20 mm, while illumination and reflectivity variations cause depth errors of less than 10 mm, provided that no overflows occurs.

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