Map Building of Unknown Environment Using L1-norm, Point-to-Point Metric and Evolutionary Computation

In the present paper, a method for building a map of an unknown environment (SLAM) derived from the ICP algorithm using point-to-point metric is proposed. The polarscan matching technology is used for estimation of the robot location change between two scans in sequence estimate the correct position of the robot. Since map building is fairly timeconsuming, the algorithm of differential evolution (DE) is used in the calculation. This efficient optimizer provides very good results in different types of small office environment (unstructured and structured). The new type of an algorithm for map building is based purely on simple geometric primitives— vectors and integrates the modern evolutionary algorithm—DE. The presented algorithm falls into the wider group of geometric map builders and is able to build a map of indoor, mostly office, environment without moving objects.