A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping

TLDR

The study proposes an incremental method for concurrent mapping and localization of mobile robots using 2D laser range finders. The method employs fast scan‑matching for mapping, a sample‑based probabilistic localization, and a multi‑resolution approach to generate compact 3D maps from dual laser data. The approach successfully builds real‑time, robust, and accurate 3D maps of large cyclic environments even without odometric data.

Abstract

We present an incremental method for concurrent mapping and localization for mobile robots equipped with 2D laser range finders. The approach uses a fast implementation of scan-matching for mapping, paired with a sample-based probabilistic method for localization. Compact 3D maps are generated using a multi-resolution approach adopted from the computer graphics literature, fed by data from a dual laser system. Our approach builds 3D maps of large, cyclic environments in real-time, and it is robust. Experimental results illustrate that accurate maps of large, cyclic environments can be generated even in the absence of any odometric data.