Alignment of Occupancy Grid and Floor Maps Using Graph Matching

Abstract

Semantic information about the environment lets users operate a robot using natural language. This is a comfortable way to make a robot do tasks in daily-life environments. Because a floor map in a building includes semantic information, if the robot can relate its own map to the floor map, the robot can access this information. The robot obtains the map of the unknown place by using simultaneous localization and mapping (SLAM). In this paper, we propose a method using graph matching to align a floor map with an occupancy grid map generated by SLAM. Our experimental results verified that this method can perform a gross alignment of the maps in an actual situation.