Application of Simultaneous Localization and Mapping in the Development of an Autonomous Robot

Abstract

Numerous industries nowadays waste considerable amounts of time, energy and money performing simple tasks that can often be allotted to service robots. The development of an affordable, open-source, autonomous indoor service robot will be of great benefit to many. An autonomous indoor service robot was developed using the Simultaneous Localization and Mapping (SLAM) Gmapping package for the Robot Operating System (ROS) and the ROS Navigation Stack. This was implemented by combining 2D LiDAR and odometry data. With this, the robot will be able to autonomously navigate and allow itself to be used in performing simple tasks from one point to another. Autonomous navigation performance was evaluated using static and dynamic obstacle tests.