Overview

Coursera Plus Annual Sale: All Certificates & Courses 25% Off!

Grab it

Embark on a transformative journey into the cutting-edge world of self-driving cars with this comprehensive specialization. Learn the core concepts, technologies, and systems that make autonomous vehicles a reality. From foundational principles to advanced decision-making, this course equips you with the expertise needed to design, implement, and test self-driving car technologies. The course begins with an introduction to autonomous vehicles, exploring their history, levels of automation, and the essential hardware and software components. Progress to system design and control systems, where you’ll master key topics like PID controllers, feedforward and feedback control, Kalman filters, and time-to-collision calculations. Delve into computer vision techniques, including object detection, semantic segmentation, and depth perception, critical for safe and accurate navigation. Engage in hands-on simulations with ROS and Gazebo, developing models, mapping environments, and implementing motion prediction. Finally, experiment with Jetbot implementation, integrating cutting-edge technologies like the Jetson Nano for real-world testing and optimization. This course is perfect for aspiring engineers, researchers, and professionals in autonomous driving. A background in programming, robotics, or vehicle dynamics is helpful but not mandatory. Suitable for intermediate learners eager to dive into the autonomous vehicle revolution.

Syllabus

Module 1 - Self Driving Car Introduction

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.

Module 2 - Self Driving Car System Design

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.

Module 3 - Control Systems

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.

Module 4 - Computer Vision

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.

Module 5: ROS Simulation

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.

Module 6 - Jetbot Implementation - Integration & Experimentation

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.