ANROL: Autonomous Navigation based on ROS and Laser Odometry

In this paper, the design and implementation of robust and precise localization and navigation scheme are proposed for an autonomous mobile robot. The proposed scheme utilizes the features of Light Detection and Ranging (LiDAR), Hector Simultaneous Mapping and Localization (SLAM), and Adaptive Monte Carlo Localization (AMCL) which is intuitively integrated with Range Flow 2D Laser Odometry (RF2O) to achieve the accuracy in the pose identification of the mobile robot. Here, the use of Hector SLAM aids in avoiding obstacles, and the use of RF2O Laser Odometry eliminates the need for additional hardware sensors for the odometry data. And thus, the proposed technique is precise and efficient in terms of power and computational complexity in a reduced form factor. The working of the developed robot is also demonstrated through the mapping and localization in a physical lab space which follows a complete close loop that ensures the accuracy and efficacy of the implemented algorithm.