When multiple robots are involved in the process of simultaneous localization and mapping (SLAM), a global map should be constructed by merging the local maps built by individual robots, so as to provide a better representation of the Drying Mat environment.Hence, the map-merging methods play a crucial rule in multi-robot systems and determine the performance of multi-robot SLAM.This paper looks into the key problem of map merging for multiple-ground-robot SLAM and reviews the typical map-merging methods for several important types of maps in SLAM applications: occupancy grid maps, feature-based maps, and topological maps.These map-merging approaches are classified based on their working mechanism or the type of features they deal with.The concepts and characteristics of these map-merging methods are elaborated in Framed Items this review.
The contents summarized in this paper provide insights and guidance for future multiple-ground-robot SLAM solutions.