ROS2 - Powered Autonomous Navigation for TurtleBot3: Integrating Nav2 Stack in Gazebo, RViz and Real-World Environments

摘要

This research focuses on developing and implementing autonomous navigation capabilities for the TurtleBot3 robot platform using Robot Operating System 2 (ROS2) and the Navigation2 (Nav2) stack. The aim is to empower the TurtleBot3 robot to achieve autonomous navigation within simulated environments crafted in Gazebo, with the visualization of the navigation process facilitated through ROS Visualization (RViz). Additionally, consideration is given to implementing these navigation capabilities in real-world scenarios. The work utilizes ROS2, known for its improved performance and scalability. The Nav2 stack, a modular and configurable navigation framework for ROS2, is employed to facilitate autonomous navigation tasks. Additionally, Gazebo is the simulation environment, providing realistic virtual environments for testing navigation algorithms. RViz is used to visualizing mapping data and navigation parameters, enhancing the understanding of the navigation process. The novelty of the work extends to both simulation and hardware implementations. The work involves loading pre-created maps, performing initial position and orientation (pose) estimation, setting navigation goals, planning paths, and executing autonomous navigation to reach specified destinations while avoiding obstacles. Key components include sensor data processing, path planning algorithms, and real-time visualization of the navigation process. Overall, this project aims to demonstrate the effectiveness of ROS2 and the Nav2 stack in enabling autonomous navigation for the TurtleBot3 robot platform in both simulated and real-world environments. To assess its efficacy in real-world scenarios, a hardware Turtlebot3 will be developed. The paper contributes to developing effective navigation solutions for robotic applications by bridging simulation and real-world scenarios.. In conclusion, this work has demonstrated the capabilities and effectiveness of real-world navigation using the TurtleBot3 platform.