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Offers a step-by-step guide to building autonomous vehicles and robots, with source code and accompanying videos The first book of its kind on the detailed steps for creating an autonomous vehicle or robot, this book provides an overview of the technology and introduction of the key elements involved in developing autonomous vehicles, and offers an excellent introduction to the basics for someone new to the topic of autonomous vehicles and the innovative, modular-based engineering approach called DragonFly. Engineering Autonomous Vehicles and Robots: The DragonFly Modular-based Approach covers everything that technical professionals need to know about: CAN bus, chassis, sonars, radars, GNSS, computer vision, localization, perception, motion planning, and more. Particularly, it covers Computer Vision for active perception and localization, as well as mapping and motion planning. The book offers several case studies on the building of an autonomous passenger pod, bus, and vending robot. It features a large amount of supplementary material, including the standard protocol and sample codes for chassis, sonar, and radar. GPSD protocol/NMEA protocol and GPS deployment methods are also provided. Most importantly, readers will learn the philosophy behind the DragonFly modular-based design approach, which empowers readers to design and build their own autonomous vehicles and robots with flexibility and affordability. Offers progressive guidance on building autonomous vehicles and robots Provides detailed steps and codes to create an autonomous machine, at affordable cost, and with a modular approach Written by one of the pioneers in the field building autonomous vehicles Includes case studies, source code, and state-of-the art research results Accompanied by a website with supplementary material, including sample code for chassis/sonar/radar; GPS deployment methods; Vision Calibration methods Engineering Autonomous Vehicles and Robots is an excellent book for students, researchers, and practitioners in the field of autonomous vehicles and robots.

The definitive resource for understanding what coding is, designed for educators and parents   Even though the vast majority of teachers, parents, and students understand the importance of computer science in the 21st century, many struggle to find appropriate educational resources. Don't Teach Coding: Until You Read This Book fills a gap in current knowledge by explaining exactly what coding is and addressing why and how to teach the subject. Providing a historically grounded, philosophically sensitive description of computer coding, this book helps readers understand the best practices for teaching computer science to their students and their children.  The authors, experts in teaching computer sciences to students of all ages, offer practical insights on whether coding is a field for everyone, as opposed to a field reserved for specialists. This innovative book provides an overview of recent scientific research on how the brain learns coding, and features practical exercises that strengthen coding skills. Clear, straightforward chapters discuss a broad range of questions using principles of computer science, such as why we should teach students to code and is coding a science, engineering, technology, mathematics, or language? Helping readers understand the principles and issues of coding education, this book: Helps those with no previous background in computer science education understand the questions and debates within the field Explores the history of computer science education and its influence on the present Views teaching practices through a computational lens Addresses why many schools fail to teach computer science adequately Explains contemporary issues in computer science such as the language wars and trends that equate coding with essential life skills like reading and writing Don't Teach Coding: Until You Read This Book is a valuable resource for K-12 educators in computer science education and parents wishing to understand the field to help chart their children’s education path.

This book is dedicated to the application of metaheuristic optimization in trajectory generation and control issues in robotics. In this area, as in other fields of application, the algorithmic tools addressed do not require a comprehensive list of eligible solutions to effectively solve an optimization problem. This book investigates how, by reformulating the problems to be solved, it is possible to obtain results by means of metaheuristics. Through concrete examples and case studies – particularly related to robotics – this book outlines the essentials of what is needed to reformulate control laws into concrete optimization data. The resolution approaches implemented – as well as the results obtained – are described in detail, in order to give, as much as possible, an idea of metaheuristics and their performance within the context of their application to robotics.