Cloud-based control and vSLAM through cooperative Mapping and Localization

Abstract

Simultaneous Localization and Mapping (SLAM) is one of the most widely popular and applied methods designed for more accurate localization and navigation operations. Our experiments showed that vision based mapping helps agents navigate in unknown environments using feature based mapping and localization. Instead of using a classical monocular camera as a vision source, we have decided to use RGB-D (Red, Green, Blue, Depth) cameras for better feature detection, 3D mapping, and localization. This is due to the fact that the RGB-D camera returns depth data as well as the normal RGB data. Moreover, we have applied this method on multiple robots using the concept of cooperative SLAM. This paper illustrates our current research findings and proposes a new architecture based on gathered data from RGB-D cameras, which are the Microsoft Kinect and the ASUS Xtion Pro for 3D mapping and localization.