Navigating the Maze Environment in ROS-2: An Experimental Comparison of Global and Local Planners for Dynamic Trajectory Planning in Mobile Robots

A critical task in the quickly developing field of robotics is efficient path planning in dynamic environments. Within the framework of ROS2 (Robot Operating System 2), this paper gives a thorough comparative analysis of several autonomous mobile robot path planning algorithms, including <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{A}^{*}$</tex>, Dijkstra, Regulated Pure Pursuit (RPP), and Dynamic Window Approach (DWA). This research investigated the effectiveness of merging local and global path planners in a dynamic maze environment using an experimental platform built on top of ROS2. Metrics include path length, deviation from the planned trajectory, and execution time. Obtained results demonstrate the performance of these algorithms highlighting their strengths and limitations while focusing on how some combinations perform better than others in terms of accuracy, planning time, and reliability.