Lidar-Based Cooperative SLAM with Different Parameters

Abstract

This paper presents a feature-based map merging approach through detecting, describing, and matching geometric features between the maps. The key contribution of this work is to identify the effective method for merging maps that are developed by varying the grid resolution and scan rate parameters. The map data sets are created by Lidar mounted on the QCar mobile robot platform. The comparison of feature detection methods to register map images at different scale is presented. Finally, the effectiveness of the proposed approach is validated based on the map fusion assumptions using real-world data. Also, SLAM (robot motion) is carried out on the merged global map (developed by proposed map fusion method).