Quark-membership-ros-roadmap

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This roadmap is designed to take you from a beginner to a confident ROS 2 developer over 12 weeks. The program combines theoretical concepts with extensive hands-on practice, using tools like Turtlesim, Gazebo, and RViz 2 to simulate and visualize real-world robotics applications.

Each session includes:

Quizzes to reinforce key concepts. Q&A Discussions to clarify doubts and deepen understanding. By the end of the program, you will have a strong foundation in ROS 2, control systems, sensor integration, and simulation tools, preparing you for practical robotics projects and applications.

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Weekly Plan sessions plan:

Weeks 1-2: Introduction to Robotics and ROS 2

• Topics:

  • Basics of Robotics, ROS 2 Overview, Installation, and Linux Basics.

• Practical Sessions:

  • Install ROS 2 Humble and test it using basic commands.
  • Explore the ROS 2 workspace.

• Assessment:

  • Quiz on ROS 2 architecture and Linux commands.
  • Q&A for installation and troubleshooting.

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Weeks 3-4: Python Refresher + ROS 2 Basics

• Topics:

  • Python fundamentals and ROS 2 Python (rclpy) client library.

• Practical Sessions:

  • Write simple Publisher and Subscriber nodes.
  • Test nodes using ros2 topic echo and ros2 topic pub.

• Assessment:

  • Quiz on Python concepts and ROS 2 message flow.
  • Q&A for debugging Python nodes.

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Weeks 5-6: ROS 2 Tools and P-Controller with Turtlesim

• Topics:

  • ROS 2 Tools (rqt_graph, ros2 topic, etc.) and control system basics (P-Controller).

• Practical Sessions:

  • Control Turtlesim using /cmd_vel commands.
  • Implement a P-Controller node to achieve a goal position.
  • Introduction to PlotJuggler:
    • Visualize real-time topic data (e.g., velocity, position).
    • Analyze the effect of Kp tuning on controller performance.

• Assessment:

  • Quiz on P-Controller concepts and ROS 2 tools.
  • Q&A for debugging and analyzing data using PlotJuggler.

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Weeks 7-8: Launch Files and ROS 2 Debugging Tools

• Topics:

  • Automating nodes with Launch Files and recording data using ros2 bag.

• Practical Sessions:

  • Write launch files to automate node execution.
  • Record and replay Turtlesim commands using ros2 bag.
  • Visualize Bag Data with PlotJuggler:
    • Load recorded data to analyze trends and system performance.

• Assessment:

  • Quiz on launch files and data recording tools.
  • Q&A for analyzing recorded data in PlotJuggler.

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Weeks 9-10: Introduction to Gazebo and Robot Simulation

• Topics:

  • Introduction to Gazebo for robot simulation and control.

• Practical Sessions:

  • Launch TurtleBot 3 simulation in Gazebo.
  • Write ROS 2 nodes to control the robot’s motion.
  • Use PlotJuggler to visualize and compare sensor data like /odom and /cmd_vel.

• Assessment:

  • Quiz on Gazebo and robot simulation basics.
  • Q&A for analyzing simulation results and debugging using PlotJuggler.

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Weeks 11-12: Sensors, Visualization, and Integration

• Topics:

  • Integrating sensors, visualizing robot states with RViz 2, and combining tools.

• Practical Sessions:

  • Launch TurtleBot 3 with sensors (Laser scanner, Camera).
  • Visualize sensor data in RViz 2.
  • Use PlotJuggler for real-time sensor data analysis.
  • Mini-Project:
    • Move TurtleBot 3 along a square path while visualizing and recording data.
    • Analyze robot performance using PlotJuggler and ros2 bag.

• Assessment:

  • Final quiz on all topics (ROS 2 basics, tools, and simulations).
  • Q&A for project demonstration and data analysis.

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Key Highlights of the Plan:

1. Smooth Progression: Starts with fundamental concepts and gradually builds toward real-world simulations.
2. Hands-On Focus: Every concept is reinforced with practical examples and mini-challenges.
3. Early Exposure to Control Systems: P-Controller with Turtlesim introduces error-based control early.
4. Incremental Tool Introduction: Tools like rqt_graph, ros2 bag, plotjuggler and launch files are integrated at the right stages.
5. Simulation and Visualization: Gazebo and RViz 2 bridge the gap between theory and real-world robotics.
6. Mini-Projects for Assessment: Weekly challenges and final demonstrations reinforce learning and provide measurable outcomes.

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