Novel point-to-point scan matching algorithm based on cross-correlation

摘要

The localization of mobile robots in outdoor and indoor environments is a complex issue. Many sophisticated approaches, basedon various types of sensory inputs and different computational concepts, are used to accomplish this task. However, many of themost efficient methods for mobile robot localization suffer from high computational costs and/or the need for high resolutionsensory inputs. Scan cross-correlation is a traditional approach that can be, in special cases, used to match temporally aligned scansof robot environment. This work proposes a set of novel modifications to the cross-correlation method that extend its capabilitybeyond these special cases to general scan matching and mitigate its computational costs so that it is usable in practical settings.The properties and validity of the proposed approach are in this study illustrated on a number of computational experiments.