Real-Time Updating of 2D Map for Autonomous Robot Locomotion Based on Distinction Between Static and Semi-Static Objects

Abstract Autonomous mobile robots are increasingly being used in complex 2D environments such as factories, warehouses, and offices. For such environments, we propose a real-time technique for updating an environmental map for a robot’s self-localization using a bearing-range sensor in situations where a basis map can be preliminarily prepared. These environments include many semi-static objects such as cardboard boxes, and the locations of these objects change frequently. Therefore, the self-localization needs to reflect the changes in both the existence and position of semi-static objects in the map in real-time. However, if the robot uses a traditional technique that updates all objects and if it keeps updating the map for a long period, static objects such as walls will move slightly on the map due to errors of both measurement and self-localization, and the map will be distorted. Therefore, our technique distinguishes between static and semi-static objects on the map, and it defines the changeability...