Metric Map Merging using RFID Tags & Topological Information
This work addresses map merging for multi-robot exploration, but it appears incremental as it combines existing techniques like RFID localization and ICP.
The paper tackles the problem of merging metric maps in multi-robot systems by proposing an approach that uses environmental information and RFID tags to calculate rotation, translation, and refine transformations with ICP, achieving unspecified accuracy improvements.
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.