Introduction

The field of robotics has experienced significant advancements, with simulation playing a vital role in developing and testing autonomous systems before their deployment in real-world scenarios. Vulcanexus (ROS 2) and Webots are two powerful tools that facilitate this process.

• Vulcanexus is a distribution of ROS 2 (Robot Operating System 2), offering enhanced performance, security, and user-friendliness for robotics applications.

• Webots is a widely used open-source robot simulator that enables developers to model, program, and simulate robotic systems in a virtual environment.

In this article, we will guide you through creating and simulating an autonomous robot using Vulcanexus (ROS 2) and Webots. At the end of this article, you should have a robot simulation similar to the one shown in the image below:

Prerequisites

Before we begin, ensure you have the following installed:

1. Vulcanexus (ROS 2 Humble) – Follow the official installation guide.

2. Webots – Download from the official website.

3. Python 3.8+ (for ROS 2 node scripting).

4. Basic knowledge of ROS 2 concepts (nodes, topics, services).

Step 1: Setting Up the Simulation Environment in Webots

Our simulation environment just requires 4 simple steps stated below

1. Launch Webots and create a new project.

2. Add a robot model (e.g., a differential drive robot).

3. Add sensors (e.g., LiDAR, cameras, IMU) to the robot.

4. Define the environment (e.g., a maze or warehouse) where the robot will operate.

1.1 Creating a New Webots Project

Launching Webots and Initial Setup

1. Open Webots: Launch the Webots application from your system menu or terminal (webots).

2. Create New Project:

   • Go to File > New Project Directory...

   • Name your project (e.g., ros2_autonomous_robot)

   • Select a location to save it

   • Click "Choose"

3. Set World Properties:

   • Webots automatically creates a default world file (worlds/.wbt)

   • Right-click the world root in the scene tree > "Edit Physics"

     • Set basicTimeStep to 32 (ms) for smooth ROS 2 integration

     • Ensure Gravity is [0, -9.81, 0]

   • Set simulation CFM to 0.00001 and ERP to 0.2 for stable physics

1.2 Building the Robot Model

Adding a Differential Drive Robot Base

1. Insert Robot Node:

   • In the scene tree, right-click "World" > "Add New" > "Robot"

   • Rename the robot node to autonomous_robot

2. Configure Robot Properties:

   • Set controller to <extern> (for ROS 2 control)

   • Enable supervisor if you need debugging capabilities

   • Set customData to ROS2 for Webots-ROS2 interface

3. Add Chassis:

   • Right-click robot > "Add New" > "Shape"

   • Under Shape:

     • Set geometry to "Box"

     • Dimensions: [0.2, 0.1, 0.3] (LWH in meters)

   • Add Appearance:

     • Set base color to your preference

     • Add PBR material for realistic rendering

Implementing Differential Drive Mechanism

1. Add Wheels:

   • Right-click robot > "Add New" > "HingeJoint" (x2)

   • For each wheel:

     • Set joint parameters:

       • anchor: [±0.1, -0.05, 0]

       • axis: [0, 1, 0]

     • Add "Solid" child with:

       • Cylinder geometry (radius: 0.05, height: 0.03)

       • Physics properties (mass: 0.5kg)

     • Add "PositionSensor" for wheel odometry

2. Configure Motors:

   • For each HingeJoint:

     • Add "RotationalMotor" device

     • Set controlPID: [10, 0, 0.1]

     • Name them left_wheel_motor and right_wheel_motor

1.3 Sensor Configuration for Autonomous Navigation

LiDAR Setup (for Obstacle Detection)

1. Add a Lidar Sensor:

   • Right-click robot > "Add New" > "Lidar"

   • Configure parameters:

     • type: "Rotating"

     • horizontalResolution: 360

     • numberOfLayers: 1

     • fieldOfView: 6.28319 (360°)

     • range: 5.0 (meters)

     • defaultFrequency: 10 (Hz)

   • Name: lidar

2. Position the Sensor:

   • Set translation to [0, 0.15, 0] (above robot)

   • Set rotation to [0, 0, 1, 0] (forward-facing)

IMU Configuration (Optional)

1. Add InertialUnit:

   • Right-click robot > "Add New" > "InertialUnit"

   • Parameters:

     • name: imu

     • frequency: 100 (Hz)

   • Position at robot's center

2. Add Accelerometer:

   • Right-click robot > "Add New" > "Accelerometer"

   • Parameters:

     • name: accelerometer

     • frequency: 100 (Hz)

Camera Setup (Optional for Vision)

1. Add RGB Camera:

   • Right-click robot > "Add New" > "Camera"

   • Configure:

     • name: front_camera

     • width: 640

     • height: 480

     • fieldOfView: 1.0472 (60°)

   • Position at front of robot

1.4 Building the Simulation Environment

Creating a Test Arena

1. Add Floor:

   • Right-click World > "Add New" > "Floor"

   • Set size: [5, 5] (5m x 5m)

   • Add Appearance with grid texture

2. Add Obstacles:

   • Insert multiple "Box" nodes:

     • Sizes between [0.2, 0.2, 0.2] to [0.5, 0.5, 0.5]

     • Scatter randomly in the arena

   • Add textured walls around the perimeter

3. Add Visual Markers (Optional):

   • Colored cylinders as navigation waypoints

   • Textured paths for line following

1.5 Final Robot Configuration

ROS 2 Interface Setup

1. Configure Proto Node:

    PROTO AutonomousRobot [
      field SFString controller "<extern>"
      field SFString customData "ROS2"
    ]
   

2. Save as Template:

   • Export your robot as a PROTO file for reuse

   • Store in protos/ directory

Step 2: Integrating ROS 2 with Webots

Webots provides a ROS 2 interface that allows communication between the simulator and ROS 2 nodes.

1. Install the Webots ROS 2 package:

    sudo apt-get install ros-humble-webots-ros2
   

2. Launch Webots with ROS 2 support:

    source /opt/ros/humble/setup.bash
    ros2 launch webots_ros2_universal_robot multirobot_launch.py
   

Step 3: Developing ROS 2 Nodes for Autonomous Control

We will create a ROS 2 node in Python to control the robot autonomously.

Example: Obstacle Avoidance Robot

1. Create a ROS 2 package:

    ros2 pkg create --build-type ament_python autonomous_robot
    cd autonomous_robot
   

2. We will write the control node in a new file in our autonomous_robot/src, create a new file, obstacle_avoidance.py The content of the new file is shown below:

    import rclpy
    from rclpy.node import Node
    from sensor_msgs.msg import LaserScan
    from geometry_msgs.msg import Twist
   
    class ObstacleAvoidance(Node):
        def __init__(self):
            super().__init__('obstacle_avoidance')
            self.subscription = self.create_subscription(
                LaserScan,
                '/scan',
                self.scan_callback,
                10)
            self.publisher = self.create_publisher(Twist, '/cmd_vel', 10)
            self.twist = Twist()
   
        def scan_callback(self, msg):
            min_distance = min(msg.ranges)
            if min_distance < 1.0:  # Obstacle detected within 1 meter
                self.twist.linear.x = 0.0
                self.twist.angular.z = 0.5  # Turn right
            else:
                self.twist.linear.x = 0.5  # Move forward
                self.twist.angular.z = 0.0
            self.publisher.publish(self.twist)
   
    def main(args=None):
        rclpy.init(args=args)
        node = ObstacleAvoidance()
        rclpy.spin(node)
        node.destroy_node()
        rclpy.shutdown()
   
    if __name__ == '__main__':
        main()
   

3. Modify setup.py to include the executable:

    entry_points={
        'console_scripts': [
            'obstacle_avoidance = autonomous_robot.obstacle_avoidance:main',
        ],
    },
   

4. Build and run the node:

    colcon build
    source install/setup.bash
    ros2 run autonomous_robot obstacle_avoidance
   

Step 4: Running the Simulation

Now that we have set up our robot in Webots and developed a ROS 2 node for obstacle avoidance, it's time to run the simulation and observe the robot in action. This step involves launching Webots, running the ROS 2 node, and verifying that the robot behaves as expected.

---

4.1 Launching Webots with ROS 2 Support

Before running the simulation, ensure that:

• Webots is installed and properly linked with ROS 2.

• The Vulcanexus (ROS 2) environment is sourced.

Steps to Launch Webots with ROS 2 Integration:

1. Open a terminal and source ROS 2:

    source /opt/ros/humble/setup.bash
   

2. Launch Webots with the robot world:

   • If you created a custom robot world in Webots, open it directly:

       webots path/to/your_robot_world.wbt
     

   • Alternatively, use a pre-built Webots ROS 2 example:

       ros2 launch webots_ros2_universal_robot multirobot_launch.py
     

3. Verify ROS 2 topics are available in Webots:

   • In Webots, go to Tools > ROS 2 Topic List to see active topics (e.g., /scan, /cmd_vel).

   • Ensure that the robot’s sensors (LiDAR, cameras) are publishing data to ROS 2 topics.

---

4.2 Running the ROS 2 Control Node

Now, let’s execute the obstacle-avoidance node we developed in Step 3.

Steps to Run the ROS 2 Node:

1. Open a new terminal and source ROS 2:

    source /opt/ros/humble/setup.bash
   

2. Navigate to your ROS 2 workspace and build the package (if not already built):

    cd ~/ros2_ws
    colcon build
    source install/setup.bash
   

3. Run the obstacle avoidance node:

    ros2 run autonomous_robot obstacle_avoidance
   

   • This node will subscribe to /scan (LiDAR data) and publish velocity commands to /cmd_vel.

4. Verify that the node is running:

   • Check active ROS 2 topics:

       ros2 topic list
     

   • Monitor /cmd_vel to see if the robot is receiving motion commands:

       ros2 topic echo /cmd_vel
     

---

4.3 Observing Robot Behavior in Simulation

Once both Webots and the ROS 2 node are running:

1. The robot should start moving forward (if no obstacles are detected).

2. When an obstacle is detected (within 1 meter, as per our code), the robot should stop and turn (angular velocity 0.5 rad/s).

3. After avoiding the obstacle, it should resume moving forward.

Debugging Tips:

• If the robot doesn’t move, check:

  • Is the /scan topic publishing data? (ros2 topic echo /scan)

  • Are there any errors in the ROS 2 node? (ros2 run autonomous_robot obstacle_avoidance should not crash)

• If the robot moves erratically, adjust the thresholds in the Python code (e.g., change min_distance < 1.0 to a different value).

---

4.4 Enhancing the Simulation (Optional)

To make the simulation more advanced, consider:

A. Adding More Sensors

• RGB Camera: For object detection (publish images to /camera/image_raw).

• IMU: For better motion control (publish to /imu/data).

B. Implementing SLAM (Simultaneous Localization and Mapping)

• Use slam_toolbox with LiDAR data to create a map.

• Run:

    ros2 launch slam_toolbox online_async_launch.py
  

C. Integrating Navigation Stack

• Use nav2 for path planning:

    ros2 launch nav2_bringup navigation_launch.py
  

Closing

Building and simulating an autonomous robot using Vulcanexus (ROS 2) and Webots opens up exciting possibilities in robotics development. By integrating ROS 2’s flexible communication framework with Webots’ realistic simulation capabilities, developers can efficiently prototype and refine robotic behaviors before deploying them in real-world scenarios.

As robotics technology continues to evolve, tools like Vulcanexus and Webots play a crucial role in accelerating innovation. Whether you're working on industrial automation, service robotics, or research projects, mastering these platforms will empower you to create smarter, more efficient robotic systems.

I hope this guide has provided you with a solid foundation for your autonomous robotics journey. Now, it’s time to experiment, iterate, and push the boundaries of what your robots can achieve! Happy coding! 🚀