Development and Testing of an Autonomous Mobile Robot for Material Handling Using SLAM and Nav2

Abstract

The adoption of Autonomous Mobile Robots (AMRs) for material handling has grown significantly across manufacturing, healthcare, and the service sector. To stay competitive in the age of automation, businesses are increasingly shifting from manual labor to AMRs to enhance the efficiency and reliability of transportation and material handling tasks. This study outlines the development of an AMR that integrates Simultaneous Localization and Mapping (SLAM), Navigation2 (Nav2), and Computer Vision (CV) to enhance material handling efficiency. The development process is structured into three distinct phases to ensure clear tracking and milestone management. In the first phase, the mobile robot is designed and developed. The second phase focuses on integrating SLAM and Nav2, enabling precise and efficient navigation within complex, dynamic environments. In the final phase, OpenCV is implemented for ArUco tag detection, enhancing the AMR’s capability to perform material handling operations. This study presents a structured approach to developing Autonomous Mobile Robots (AMRs) equipped with real-time obstacle detection, avoidance, path planning, and material handling capabilities, streamlining deployment in real-world applications.