Rapid SLAM using simple map representation in indoor environment

Simultaneous Localization and Mapping is the one of essential techniques for mobile robot navigation. In this paper, we propose rapid SLAM using simple map representation in indoor environment for mobile robot. This approach offers a new way to look at the problem focusing on the issues that have caused the use of 3D laser scanner which provide lot of 3D point data. We have tried to create the simple segments of line and range table for scan-matching in a way that allows a robust solution to the problem. In this article, two important issues of this work on 2D registrations are made. First, it is shown that the algorithm performs very well on the transformations of segmented line map from lot of 3D point cloud data. Second the mapping logic and sequence are explained in this paper to a line component accumulation for a map building. Experimental results from 3-D sensor Velodyne and wheel-odometry data logger Racelogic Vbox are given. Experimental results show that this approach is not only robust for line mapping but it is also fast, requires significantly less memory.