Introduction

The robot_sensing package is designed to simulate and control robots equipped with various sensors, particularly in environments like mazes and line-following tracks. This package provides launch files and nodes for maze solving using LIDAR and line following using a camera sensor. It serves as an educational tool for understanding how sensors can be used to guide robots in complex environments using ROS 2.

How to Run

System Requirements: ROS 2 Humble on Ubuntu 22.04 (tested).

To build the package:

colcon build --packages-select robot_sensing

To source the setup file:

source install/setup.bash

Running Simulations

• Maze Solving with LIDAR:

  ros2 launch robot_sensing lidar_maze_solving.launch.py
  

• Line Following with Camera:

  ros2 launch robot_sensing camera_line_following.launch.py
  

• Custom Sensor Setup in Gazebo:

  ros2 launch robot_sensing custom_sensors.launch.py
  

Note: File names might have changed since the initial lectures, as this represents the final form of the package as it evolved by the last lecture.

Source Files and Launch Files

Source Files

1. line_following_with_camera.cpp
   • Purpose: Implements the logic for a robot to follow a line using input from a camera sensor. The algorithm processes the camera feed to detect the line and generate velocity commands to keep the robot on track.
   • Algorithm: Uses computer vision techniques to identify the line and a proportional controller to adjust the robot’s steering based on the line’s position relative to the robot.
2. maze_solving_with_lidar.cpp
   • Purpose: Implements a maze-solving algorithm that uses LIDAR data to navigate through a maze. The robot scans its environment and makes decisions based on detected obstacles.
   • Algorithm: The robot uses a wall-following algorithm, combined with LIDAR data, to systematically explore and find the exit of the maze.

Launch Files

1. camera_line_following.launch.py
   • Purpose: Launches a simulation environment for line following using a camera in Gazebo.
   • Nodes Launched:
     • robot_state_publisher - Publishes the robot’s URDF to the TF tree.
     • gazebo_ros - Spawns the robot in a Gazebo world configured for line following.
     • line_following - The node that controls the robot to follow the line based on camera input.
2. lidar_maze_solving.launch.py
   • Purpose: Launches a maze-solving simulation using LIDAR data in Gazebo.
   • Nodes Launched:
     • robot_state_publisher - Publishes the robot’s URDF to the TF tree.
     • gazebo_ros - Spawns the robot in a Gazebo world configured as a maze.
     • maze_solver - The node that drives the robot through the maze using LIDAR input.
3. custom_sensors.launch.py
   • Purpose: Launches a custom sensor setup in Gazebo, allowing for the simulation of different sensors on the robot.
   • Nodes Launched:
     • robot_state_publisher - Publishes the robot’s URDF to the TF tree.
     • joint_state_publisher - Publishes joint states for the robot in Gazebo.
     • gazebo_ros - Spawns the robot in Gazebo with custom sensor configurations.

Package Dependencies

The CMakeLists.txt file specifies the necessary dependencies for building and running the robot_sensing package:

• Dependencies:
  • rclcpp - ROS 2 C++ API for creating nodes, publishers, and subscribers.
  • sensor_msgs - ROS 2 message types for handling sensor data.
  • geometry_msgs - ROS 2 message types for geometry data, including velocity commands for the robot.
  • gazebo_ros - Integration with the Gazebo simulator for launching and controlling the robot in a simulated environment.

Test your Learnings with Assignments

• Assignment