Hybrid Scheme for Indoor Localization and Map Building with a Laser Range Finder and a Local Positioning Sensor

Abstract

Localization and map building in indoor environments are important problems for mobile robots. There are two approaches to address these problems: a metric approach and a topological approach. The metric approach uses various range sensors to determine the distance between an obstacle and the robot for precise localization of the robot whereas the topological approach gives the robot its status on the basis of landmarks. As both approaches have respective advantages and disadvantages, researchers in the field of mobile robotics have integrated the two approaches to allow robots to explore their environment autonomously. This so called hybrid approach still requires additional odometric information for rapid convergence of robot positioning, as well as information to facilitate landmark recognition. To build a more accurate map and to precisely localize the position and orientation of the robot, we use a local positioning sensor to compensate for the accumulation of wheel encoder errors and landmark recognition errors. We also propose a new method that fuses a laser range finder, a local positioning sensor, and wheel encoders. The experimental results confirm that the robot can construct its own environment and localize itself accurately and consistently.