ROS-base Multi-Sensor Fusion for Accuracy Positioning and SLAM System

Abstract

To facing lower birth rate and aging society trend, how to design intelligent robots demanded in different fields to reduce the shortage of human resource has become an one of important research topics in recent years. In order to satisfy mobility ability of intelligent robots, accurate indoor positioning is an important function.In this paper, we use the Robot Operation System(ROS) as our platform, combining with different positioning sensors and technologies, such as Light Detection and Ranging(LiDAR), Inertial Measurement Unit (IMU), odometer and Ultra-wideband(UWB), and fuse these data by Extended Kalman Filter(EKF) to provide accuracy positioning. Thus, we can achieve more refined Simultaneous Localization and Mapping(SLAM) which meets the intelligent robot application demand. Experiment results show that the average error distance of the mobile robot in our system can be limited in 10cm.