SLAM-Based Indoor Navigation with LiDAR and ROS2 for Autonomous Mobile Robot

Abstract

While robots have been able to provide insights into solutions to the inefficiency, safety, and adaptability of operational and logistic related engagements, sensor reliability, accuracy, and navigation in dynamic environments are some of the challenges that have limited their performance. This paper focuses on developing an Autonomous Mobile Robot (AMR) that can enhance logistics and operational efficiency. By utilizing the Robot Operating System (ROS) along with key components like Light Detection and Ranging (LiDAR), Raspberry Pi, and microcontrollers, the robot is developed to autonomously navigate complex environments. The performance of the developed robot is studied in terms of its ability to achieve 360 degrees of view and avoid obstacles through successive mapping and navigation in an arbitrary environment. In simulation and limited real-world trials, the system achieved reliable indoor navigation; we report configuration details and reproducibility artifacts.