In this module, we will embark on an introductory journey into the world of Self-Driving Cars. Starting with their definition and historical evolution, we’ll explore the key technologies and safety standards that underpin their functionality. Additionally, we will cover typologies, decision-making processes, and the hardware and software that bring these revolutionary vehicles to life.

In this module, we will delve into the essential design elements of Self-Driving Car systems. We’ll explore the hardware components that provide sensory input, the software systems that process data and manage driving tasks, and the architectural design that ensures seamless interaction between these elements. This comprehensive overview will lay the foundation for understanding how Self-Driving Cars operate as a cohesive unit.

In this module, we will explore the intricate control systems that drive Self-Driving Cars. We’ll start with longitudinal control, Adaptive Cruise Control, and state estimation techniques before delving into advanced topics such as Kalman Filters, motion prediction, and collision detection. Additionally, we’ll introduce ROS simulation tools to develop and optimize these systems. By mastering these concepts, you'll gain a comprehensive understanding of the control mechanisms essential for autonomous vehicles.

In this module, we will explore the world of computer vision, a critical component of Self-Driving Car technology. We’ll cover foundational concepts like object detection, tracking, and semantic segmentation, before diving into advanced techniques such as 3D object detection, HydraNets, and stereo vision. Finally, we’ll examine the integration of real-time vision depth perception using platforms like Jetson Nano, showcasing their impact on autonomous vehicle navigation and safety.

In this module, we will master ROS simulations, a cornerstone of Self-Driving Car development. Starting with the setup of ROS2 and Gazebo, we’ll explore how to create model cars, roads, and detailed environments for realistic simulations. Additionally, we’ll delve into advanced topics such as motion prediction, state estimation, obstacle avoidance, and localization, providing a comprehensive toolkit for testing and refining autonomous vehicle systems.

In this module, we will explore the practical application of Self-Driving Car concepts using the Jetbot platform. Starting with the setup and assembly of the Jetson Nano and Jetbot hardware, we’ll dive into functionalities like collision avoidance, road and object following, and real-time vision depth perception. The module culminates in testing the fully integrated Jetbot system in real-world environments, providing hands-on experience in robotics experimentation and validation.