LiDAR-Based Smart Navigation and Mapping for Mobile Robot on ROS

In this paper, we investigate the adaptability of a SLAM-based mobile robot for the purpose of mapping and navigating within indoor environments. The robot operates on the Robot Operating System (ROS) framework, with its model constructed using the Gazebo package and simulated in Rviz. The mapping process involves the use of the open-source Hector SLAM algorithm. The primary objective of this paper is to evaluate the mapping, localization, and navigation capabilities of a mobile robotic model within unfamiliar environments. Additionally, real-time path planning is examined to assess the quality of the mapping results. Global path planning makes use of the A ∗ algorithm to strike a balance between path optimality and obstacle avoidance, whereas the DWA algorithm is employed for local path planning. To validate the proposed techniques, experiments have been carried out in indoor environments to confirm their effectiveness and reliability.