A localization and navigation method with ORB-SLAM for indoor service mobile robots

Autonomous mobile robots need to acquire environment information for localization and navigation, and thus are usually equipped with various sensors. Consequently, the system is complex and expensive, bringing obstacles for general home applications. In this paper, we present an efficient, yet economic and simple solution for indoor autonomous robots, consisting of a basic mobile platform, a Kinect V2 sensor and a computing unit running Linux. Within the ROS environment, the ORB-SLAM algorithm, pointcloud processing methods and a feedback controller have been developed and implemented respectively for localization, obstacle detection and avoidance, and navigation. Experimental results showed robust localization, safe and smooth navigation, good motion control accuracy and repeatability, demonstrating the efficacy of the system architecture and algorithms.

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