A ROS-2 based Path Planning and Maze Solving of Autonomous Robots

Abstract

The goal of this study is to build a self-driving robot that can effectively navigate mazes by utilizing sophisticated computer vision algorithms with ROS2. Fusion 360 is used to create the robot model, and ROS2 launch files are used to initialize the sensor and control nodes. Attaining optimal path planning and accurate localization are the main objectives. The combination of novel motion planning based on the orientation of the robot with graph search algorithms like DFS, A*, and Dijkstra's leads to effective maze discovery and traversal. Thorough testing shows that the system can successfully navigate unfamiliar maze configurations, demonstrating the dependability of ROS2 and modern robotics techniques. By completing this study, a foundation for future advancements in perception and planning to manage more complex settings is laid.