SLAM-Based 2D Mapping and Route Planning for Autonomous Mobile Robot Navigation

Abstract

Autonomous mobile robots are increasingly deployed in residential, commercial, industrial, and logistics settings. To navigate these environments effectively, they require accurate mapping, obstacle detection, and optimized path planning. This study presents an integrated navigation system combining SLAM (Simultaneous Localization and Mapping), 2D occupancy grid mapping, and Dijkstra’s algorithm for global route planning, implemented using MATLAB. Experiments conducted in a simulated warehouse environment at the Federal University of Viçosa demonstrated the system’s ability to accurately map the environment, detect obstacles, and execute planned trajectories with high fidelity. The results highlight the effectiveness of using MATLAB in conjunction with ROS for rapid development and real-time control in mobile robotics applications.