Metric Map Merging using RFID Tags & Topological Information

TL;DR

This paper presents a novel metric map merging method for multi-robot exploration that utilizes RFID tags and topological data to accurately align and integrate individual maps, enhancing collaborative exploration.

Contribution

It introduces a new map merging approach combining RFID tag localization, obstacle pose analysis, and ICP refinement, advancing multi-robot map integration techniques.

Findings

Effective RFID-based localization improves map alignment accuracy.

Combining topological and metric data enhances merging robustness.

The method supports scalable multi-robot exploration systems.

Abstract

A map merging component is crucial for the proper functionality of a multi-robot system performing exploration, since it provides the means to integrate and distribute the most important information carried by the agents: the explored-covered space and its exact (depending on the SLAM accuracy) morphology. Map merging is a prerequisite for an intelligent multi-robot team aiming to deploy a smart exploration technique. In the current work, a metric map merging approach based on environmental information is proposed, in conjunction with spatially scattered RFID tags localization. This approach is divided into the following parts: the maps approximate rotation calculation via the obstacles poses and localized RFID tags, the translation employing the best localized common RFID tag and finally the transformation refinement using an ICP algorithm.