SLAM of Robot based on the Fusion of Vision and LIDAR

Abstract

The Simultaneous Localization and Mapping (SLAM) of robots plays an increasingly important role in the development of mobile robots. The two most commonly used methods are visual and LIDAR methods. In the visual design, the RGB-D camera is sensitive to light, and it has a narrow field of vision. Besides, in the featureless environment, it is difficult to extract visual features. The confines above lead to a poor tracking in practice, which causes a failure in mapping completely. This paper aims at the tracking part of SLAM using an RGB-D camera and 2d low-cost LIDAR to finish a robust indoor SLAM by a mode switch and data fusion. The experiment shows that our method can get an effect map even in the featureless environment.