This project implements an autonomous RC car using ROS 2 (Humble), combining simulation, perception, and navigation into a complete robotic system. The vehicle is modeled with an Ackermann steering system and equipped with a LiDAR sensor for environment perception.
The system is simulated in Gazebo, where realistic physics and sensor data are generated, and visualized in RViz for real-time monitoring of LiDAR data, TF frames, and mapping results. Using SLAM Toolbox, the robot builds a 2D map of its environment while estimating its position.
The project demonstrates a full autonomous robotics pipeline:
Simulation → LiDAR Perception → SLAM → Mapping → Navigation (Nav2)
This work serves as a foundation for scalable autonomous driving systems and showcases the integration of robotics and AI techniques in a controlled environment.
Remember that you need to add the visualizations inside rviz, such as robot description, laser, map.
ros2 launch maqui_na launch.sim.launch.py world:=../src/maqui_na/worlds/maqui_na_saved.world
By writting this code in the terminal, you will be able bridge Gazebo and Ros2. Keep in mind that you will have to open rviz separately. You must add the robot description in order to see the URDF of the robot.
ros2 run joint_state_publisher_gui joint_state_publisher_gui
Will be need it to visualize the TF of the robot.
The list below contains the commands used to visualize the SLAM algorithm:
New Slam Map
ros2 launch slam_toolbox online_async_launch.py params_file:=./src/maqui_na/config/mapper_params_online_async.yaml use_sim_time:=true
Saved Slam Map
ros2 launch slam_toolbox localization_launch.py \ slam_params_file:=/home/angello/thesis/src/maqui_na/config/mapper_params_online_async.yaml \ use_sim_time:=true
ros2 launch slam_toolbox localization_launch.py \ "slam_params_file:=/home/angello/thesis/src/maqui_na/config/mapper_params_online_async.yaml" \ "use_sim_time:=true"
Running Nav2
ros2 run nav2_map_server map_server --ros-args -p yaml_filename:=maqui_na_save.yaml -p use_sim_time:=true
Activation of The Saved Map
ros2 run nav2_util lifecycle_bringup map_server
Activate AMCL
ros2 run nav2_amcl amcl --ros-args -p use_sim_time:=true
To Activate AMCL, afterwards 2D position arrow estimation.
ros2 run nav2_util lifecycle_bringup amcl
Twist Mux
ros2 run twist_mux twist_mux --ros-args --params-file ./src/maqui_na/config/twist.mux.yaml -r cmd_vel_out:=diff_cont/cmd_vel_unstamped
Nav2 Navigation Launch
ros2 launch nav2_bringup navigation_launch.py use_sim_time:=true