Research on Autonomous Navigation of Showroom Service Robot Based on ROS and Laser SLAM

Abstract

As an important tool for guiding and introducing visitors to the exhibition hall, the robot needs to confront the complex environment that may exist and the constantly moving visitors. First of all, it is needed to have the ability to enable accurate positioning and navigation as well as dynamic obstacle avoidance. In recent years, simultaneous localization and mapping (SLAM) technology has been widely used to address localization and navigation issues in unknown indoor environments. Based on the robot operating system (ROS), this study collects environmental information by 2D LiDAR, and then combines the service robot's Inertial measurement unit (IMU), odometer, and other sensors to map the exhibition hall environment by the Cartographer SLAM algorithm. Path planning and dynamic obstacle avoidance functions are also implemented, in path planning, the algorithm is selected for global path planning and the Dynamic Window Approach (DWA) algorithm for local path planning. The environment map construction, path planning and dynamic obstacle avoidance functions are verified by simulation and in real environment. The average position deviation and standard deviation (SD) of the robot from the target point were less than 7 cm and less than 3 cm, respectively, when the robot was set to move at 0.5 m/s for the positioning test. The average heading deviation was less than 9° and SD was less than 3°. The robot's positioning and navigation can well meet the working requirements of the pavilion service robot.