AuNa: Autonomous Navigation System Simulator

A comprehensive ROS2-based framework for autonomous vehicle simulation, featuring cooperative driving scenarios, multi-robot coordination, and advanced navigation algorithms. The system uses Docker Compose for easy deployment and provides Gazebo simulation with RViz visualization.

🚀 Key Features

• Multi-Robot Simulation: Support for multiple autonomous vehicles in coordinated scenarios
• CACC Implementation: Cooperative Adaptive Cruise Control for platooning scenarios
• Advanced Navigation: Integration with ROS2 Navigation2 stack for path planning and obstacle avoidance
• Wall Following: Robust wall-following algorithms using LIDAR data
• Docker-based Deployment: Simple containerized deployment - no manual installation required
• Real-time Visualization: Gazebo 3D simulation with RViz integration

🛠️ Installation

Prerequisites: Docker with docker compose support

1. Clone the repository:

   git clone https://github.com/HarunTeper/AuNa.git
   cd AuNa
   

🚀 Usage

Running Simulations

The only supported method is through Docker Compose.

Important: Before running a scenario, configure the world in the .env file:

1. Edit the .env file in the project root:

   # For racing scenario
   WORLD_NAME=racetrack_decorated
   
   # For platooning scenario
   WORLD_NAME=arena
   

1. Launch the scenario:

Racing Scenario (1 robot)

Set WORLD_NAME=racetrack_decorated in .env, then run:

docker compose --profile racing up

Platooning Scenario (3 robots)

Set WORLD_NAME=arena in .env, then run:

docker compose --profile platooning up

Available Worlds

• racetrack_decorated - Racing track environment (default for racing)
• arena - Open arena environment (default for platooning)

After launching, Gazebo and RViz windows will start automatically.

🎮 RViz Configuration

Once the simulation starts, you’ll see both Gazebo (simulation) and RViz (visualization) windows.

Setting Up Robot Namespace in RViz

1. Enter the namespace in RViz for each robot you want to control:
   • Format: robot + index (starting from 1)
   • Examples: robot1, robot2, robot3
2. Select input source after entering the namespace:
   • Default: off (no autonomous control)
   • Available sources:
     • wallfollowing - Follow walls using LIDAR
     • teleop - Manual keyboard control
     • nav2 - Navigation2 path planning
     • cacc - Cooperative Adaptive Cruise Control

Robot Role Configuration

Leader Robot (robot1)

For racetrack_decorated world:

• Use wallfollowing for autonomous wall following
• Use nav2 for goal-based navigation

For arena world:

• Use nav2 for goal-based navigation
• Use cacc for coordinated movement

Follower Robots (robot2, robot3, …)

For all worlds:

• Use cacc for following the leader robot in formation

Example Usage Flow

File truncated at 100 lines see the full file

Any contribution that you make to this repository will be under the MIT license, as dictated by that license.