Localization and modelling approach using topo-geometric maps

Abstract

Simultaneous localization and mapping (SLAM) is one of the fundamental problems in mobile robots. In this paper we present a new SLAM algorithm in an unknown indoor environment. A local Voronoi diagram (LVD) is built from a laser scanner measurements, in order to estimate the robot position using its topological and geometrical characteristics. The proposed algorithm introduces a backward step, which revises all previous poses. This step is fundamental to obtain good results in large and cyclic indoor environments. Genetic algorithms are used in order to improve the estimated approach.