AI Consulting and Training Club, Bahria Town Lahore

Category: Courses

  • ROS Autonomous Vehicles 101 – Artificial Intelligence

    ROS Autonomous Vehicles 101: A 4-Month Self-Study Course

    Course Syllabus

    Course Description

    Welcome to “ROS Autonomous Vehicles 101”! This comprehensive 4-month self-study course is meticulously designed to transform you from a motivated beginner into an intermediate expert in the exciting and rapidly evolving field of autonomous vehicles, utilizing the powerful Robot Operating System (ROS).

    Through a dynamic blend of essential theoretical concepts and engaging, hands-on examples, you will build a robust foundation in the core principles of autonomous navigation, perception, and control—all seamlessly integrated within the versatile ROS ecosystem. By the conclusion of this course, you will not only understand but also be proficient in implementing fundamental autonomous vehicle behaviors, setting the stage for more advanced endeavors in robotics.

    Primary Learning Objectives

    Upon successful completion of this course, you will be able to:

    1. Grasp the fundamental architecture and crucial components of ROS as they specifically apply to autonomous vehicles.
    2. Skillfully configure and launch basic ROS nodes for effective vehicle simulation and real-world control.
    3. Proficiently implement basic navigation stacks, encompassing mapping, localization, and sophisticated path planning techniques.
    4. Effectively utilize various sensors (e.g., LiDAR, cameras, IMU) for critical perception tasks in autonomous driving scenarios.
    5. Develop, debug, and seamlessly integrate robust control algorithms for precise vehicle motion.
    6. Rigorously simulate and thoroughly test autonomous vehicle behaviors within realistic and challenging environments.
    7. Efficiently debug and troubleshoot complex ROS-based autonomous vehicle systems.
    8. Design, develop, and execute a comprehensive cumulative final project that brilliantly demonstrates core autonomous vehicle functionalities.

    Necessary Materials

    • A high-performance computer with sufficient processing power (minimum 8GB RAM, Intel i5 processor or equivalent recommended for optimal performance).
    • Ubuntu 20.04 LTS (Focal Fossa) or a later stable release.
    • ROS Noetic or ROS2 Foxy/Galactic installed (ROS Noetic will be the primary focus for ROS1 topics, with an introduction to ROS2 for newer concepts).
    • Gazebo simulation environment (latest stable version recommended).
    • RViz visualization tool.
    • Python 3 and C++ compilers (pre-installed with ROS).
    • Reliable internet access for additional resources, documentation, and seamless package installations.
    • (Optional but Highly Recommended) A basic ROS-compatible mobile robot platform (e.g., TurtleBot3) for invaluable real-world testing and application.

    Course Content

    This comprehensive course is thoughtfully structured into 14 distinct weekly lessons, allowing for two dedicated buffer weeks within the 16-week timeframe. These buffer weeks can be utilized for in-depth review, deeper dives into complex topics, or catching up on challenging material, ensuring a flexible and effective learning pace.

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    Week 1: Introduction to Autonomous Vehicles and ROS Fundamentals

    • Title: The Road Ahead: Understanding Autonomous Vehicles and ROS
    • Learning Objectives:
      • Clearly define what constitutes an autonomous vehicle and articulate its various levels of autonomy.
      • Provide a comprehensive explanation of the core concepts and modular architecture of the Robot Operating System (ROS).
      • Efficiently set up a basic ROS development environment and thoroughly verify its correct installation and functionality.
    • Key Vocabulary:
      • Autonomous Vehicle: A self-governing vehicle capable of perceiving its surroundings and operating without direct human intervention.
      • ROS (Robot Operating System): A flexible and widely adopted framework for writing sophisticated robot software, comprising a rich collection of tools, libraries, and standardized conventions to simplify the development of complex and robust robot behaviors across diverse robotic platforms.
      • Node: An independent, executable process within ROS that performs specific computational tasks.
      • Topic: A named communication channel over which ROS nodes asynchronously exchange messages.
      • Message: A structured data format utilized for reliable communication between distinct ROS nodes.
      • roscore: The essential master node that enables all other ROS nodes to discover each other and facilitate message exchange within the ROS graph.
    • Content:

      Autonomous vehicles are at the forefront of a technological revolution, promising unprecedented advancements in transportation through increased safety, enhanced efficiency, and improved accessibility. But what fundamental elements truly define an “autonomous” vehicle? This week, we will delve into the intricate layers of autonomy, ranging from advanced driver-assistance systems (ADAS) to fully self-driving cars, and explore the complex interplay of perception, intelligent decision-making, and precise control that underpins their functionality.

      At the very heart of numerous cutting-edge robotic and autonomous vehicle projects lies ROS. ROS provides an unparalleled standardized framework for developing robot software, empowering developers to efficiently reuse code, leverage powerful tools, and adapt proven algorithms. Envision ROS as a comprehensive operating system specifically designed for robots, offering essential services such as hardware abstraction, low-level device control, implementation of common functionalities, robust message-passing mechanisms, and streamlined package management. We will commence by thoroughly understanding its modular architecture, with a dedicated focus on the pivotal concepts of nodes, topics, and messages—the foundational building blocks that enable all ROS communication.

      Establishing your ROS environment correctly is the initial and most critical step. We will guide you through the meticulous installation process for Ubuntu and ROS (specifically emphasizing ROS Noetic, a widely utilized and stable version for many contemporary robotics projects). Furthermore, we will introduce you to indispensable ROS command-line tools that empower you to interact seamlessly with the system, including roscore, rosnode, rostopic, and rosmsg. These commands serve as your indispensable gateway to initiating ROS, inspecting active nodes, visualizing data flowing across topics, and comprehending intricate message definitions.

      Example: Consider a self-driving car that requires real-time knowledge of its current speed. A dedicated “Speed Sensor Node” could continuously publish the vehicle’s speed data on a ROS topic named “/car_speed”. Subsequently, a “Control Node” could subscribe to this topic to receive the speed information and dynamically adjust the throttle input, ensuring optimal vehicle control. This inherent modularity is a cornerstone of ROS’s immense power and flexibility.

    • Hands-on Example:
      1. Perform a complete installation of ROS Noetic on your Ubuntu system (if not already installed). Follow the official ROS Noetic installation guide for precise instructions.
      2. Initiate roscore in your primary terminal window.
      3. Open a new terminal and meticulously create a simple ROS Python script (e.g., publisher_node.py) that publishes a “Hello World” string message on a topic named /chatter at a consistent rate of 1 Hz.
      4. Create another ROS Python script (e.g., subscriber_node.py) that subscribes to the /chatter topic and prints every received message to the console.
      5. Execute both nodes concurrently and carefully observe the messages being continuously printed by the subscriber node.
      6. Utilize the commands rostopic list, rostopic info /chatter, and rostopic echo /chatter to comprehensively inspect the topic and its exchanged messages.

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    Week 2: Gazebo and RViz: Simulation and Visualization

    • Title: Virtual Worlds, Real Insights: Simulating and Visualizing with Gazebo and RViz
    • Learning Objectives:
      • Thoroughly understand the pivotal role of Gazebo for accurately simulating robotic environments and diverse sensor modalities.
      • Gain proficiency in launching and interactively manipulating Gazebo simulations.
      • Master the utilization of RViz for compelling visualization of sensor data, intricate robot models, and dynamic navigation trajectories.
    • Key Vocabulary:
      • Gazebo: A sophisticated 3D simulator renowned for its ability to create realistic robotic environments and accurately model complex physical interactions.
      • RViz: A powerful and versatile 3D visualization tool specifically designed for ROS, enabling dynamic display of sensor data, detailed robot models, and much more.
      • URDF (Unified Robot Description Format): An XML-based file format universally used for comprehensively describing the physical and kinematic properties of a robot model.
      • TF (Transformations): A fundamental ROS package dedicated to efficiently tracking coordinate frames and their transformations over time, crucial for understanding spatial relationships in robotics.
    • Content:

      The development of advanced autonomous vehicles necessitates extensive and rigorous testing. However, conducting such tests exclusively in the real world can be prohibit