Ackermann Steering Vehicle Simulation in ROS2 with Gazebo Sim Harmonic

This project features the simulation of a custom vehicle with Ackermann steering capabilities, developed using ROS2 and the Gazebo Sim Harmonic environment. The model integrates a variety of sensors and navigation tools for autonomous operation, making it one of the first implementations of an Ackermann steering vehicle in this simulation framework.

Features

1. Ackermann Steering

• A custom vehicle model built with realistic Ackermann steering dynamics for accurate maneuverability.

2. ROS2 Communication

• All sensor data and control signals are fully integrated into the ROS2 ecosystem for seamless interoperability.

3. Sensors

• IMU: Provides orientation and angular velocity.
• Odometry: Ensures accurate vehicle state feedback.
• LiDAR: Mounted for obstacle detection and environmental scanning.
• Cameras:
  • Front-facing
  • Rear-facing
  • Left-side
  • Right-side

4. Navigation

• Integrated with the Nav2 stack for autonomous navigation.
• AMCL (Adaptive Monte Carlo Localization) for improved positional accuracy.
• SLAM techniques implemented for real-time mapping and understanding of the environment.
• Fine-tuned parameters for optimized navigation performance.

5. Manual Control (with external joystick)

• Added support for joystick-based manual control in the simulation environment, enabling users to test vehicle movement interactively.

6. Visualization

• Full model and sensor data visualization in RViz2, providing insights into robot states and environmental feedback.

Requirements

• ROS2 (Humble)
• Gazebo Sim Harmonic
• RViz2
• Nav2

Installation and Usage

Run the following commands to set up and launch the simulation:

0. Your need to sure that installation of Gazebo Harmonic and ROS (ros_gz):
   sudo apt-get install ros-${ROS_DISTRO}-ros-gz
sudo apt-get install ros-humble-ros-gzharmonic(Only Humble version)
   More details about installation Gazebo and ROS: Link

1. Clone the repository:
   mkdir -p ackermann_sim/src && cd ackermann_sim/src
git clone https://github.com/alitekes1/ros2-ackermann-vehicle-gz-sim-harmonic-nav2
cd ..

2. Build the project: colcon build && source install/setup.bash

3. Set environment variables:

   # Set environment variables for current session
   export GZ_SIM_RESOURCE_PATH=$GZ_SIM_RESOURCE_PATH:/your/path/ackermann_sim/src/ros2-ackermann-vehicle-gz-sim-harmonic-nav2/
   export ROS_PACKAGE_PATH=$ROS_PACKAGE_PATH:/your/path/ackermann_sim/src/ros2-ackermann-vehicle-gz-sim-harmonic-nav2/

   For Permanent Setup:

   To make these environment variables permanent, add them to your .bashrc file:

   # Add environment variables to .bashrc
   echo 'export GZ_SIM_RESOURCE_PATH=$GZ_SIM_RESOURCE_PATH:/your/path/ackermann_sim/src/ros2-ackermann-vehicle-gz-sim-harmonic-nav2/' >> ~/.bashrc
   echo 'export ROS_PACKAGE_PATH=$ROS_PACKAGE_PATH:/your/path/ackermann_sim/src/ros2-ackermann-vehicle-gz-sim-harmonic-nav2/' >> ~/.bashrc
   
   # Apply changes
   source ~/.bashrc

   Note: Replace /your/path/ with your actual installation path.

4. Launch the simulation: ros2 launch saye_bringup saye_spawn.launch.py

5. Control car: ros2 run teleop_twist_keyboard teleop_twist_keyboard

Note: By default, only the front camera is bridged to ROS 2.
If you want to use all cameras (left, right, rear) in ROS 2,
remove the # at the beginning of the relevant camera sections in
saye_bringup/config/ros_gz_bridge.yaml to activate them
(e.g., /camera/left_raw, /camera/right_raw, /camera/rear_raw).

Future Work

1. Deep Reinforcement Learning (DRL):
   • Train the vehicle to handle complex scenarios autonomously using advanced DRL algorithms.
2. Enhanced Features:
   • Explore additional sensor configurations and navigation strategies.

Gallery

Gazebo Sim Harmonic	RViz2

TF Tree

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