A strategic methodology for 2D map building in an Indoor environment

This paper presents how to construct 2D map using SICK LMS 100 Laser Range Finder (LRF) in an Indoor environment. Objects in the environment are represented by different line segments and are treated as different features. This paper presents different steps to be followed to develop a local map out of the Laser data and later on global map by correctly stitching the numerous local maps obtained by processing consecutive Laser scans. The Laser data obtained in Polar coordinates are converted into Cartesian coordinates and mapped. Different objects are mapped on the basis of four quadrant system. Errors in mapping, basically in global mapping are recognized and attempted to minimize. Odometry data plays a vital role in global mapping but is susceptible to errors. These odometric errors are eliminated by integrating Kalman Filter data with odometric data. Also hardware set up with Linux platform and real-time Laser data processing is discussed in brief.