Autonomous Indoor Navigation Using Nav2

The project focuses on the design, development, and implementation of an Autonomous Mobile Robot (AMR) system specifically tailored for warehouse environments. The escalating demand for efficient warehouse management, driven by the e-commerce boom, necessitates the adoption of automated solutions to overcome challenges like labor shortages and operational inefficiencies. The proposed AMR system integrates advanced sensing technologies, including 2D LiDAR and IMU, with robust navigation and control algorithms to enable the robot to autonomously navigate through dynamic warehouse environments. The core of the system is built upon the ROS 2 framework, providing a robust and flexible platform for development and deployment. The project explores the implementation of Simultaneous Localization and Mapping (SLAM) techniques, utilizing the SLAM Toolbox, to enable the robot to build and update maps of its environment while simultaneously determining its position. Furthermore, the system incorporates advanced path planning algorithms and obstacle avoidance mechanisms to ensure safe and efficient navigation. The project utilizes Gazebo for realistic simulation and validation, allowing for thorough testing and optimization of the AMR system before real-world deployment. This research aims to contribute to the advancement of warehouse automation by developing a cost-effective and efficient AMR system that can significantly improve operational efficiency and productivity.