In recent years, developing efficient autonomous navigation systems for robots has become increasingly important, particularly in dynamic environments. This research paper describes an advanced autonomous navigation system designed for the TurtleBot3 Waffle, equipped with LiDAR and camera attachments. Our research focuses on enhancing robot navigation skills in dynamic situations by leveraging the cutting-edge ROS2 Navigation2 stack. We extensively tested our system on five different map configurations, with an average response time of 1.2s, demonstrating its effectiveness. One of our system’s distinguishing characteristics is integrating voice command control to enable seamless interaction with the robot. A ROS2 node utilizing Pocket Sphinx for speech recognition supports over 100 voice commands, including forward, backward, left, right, and return functions. This feature allows the TurtleBot to navigate autonomously while responding accurately to real-time voice commands. This research advances autonomous robotics by combining state-of-the-art navigation algorithms with intuitive voice control, paving the way for more efficient robotic systems. Potential applications include healthcare assistance, industrial automation, and smart home systems, highlighting the broad impact of this technology.