• Title Elements of Robotics
• Author(s) Mordechai Ben-Ari and Francesco Mondada
• Publisher: Springer; 1st ed. 2018 Edition; eBook (Creative Commons Licensed)
• License(s): CC BY 4.0
• Hardcover/Paperback: 324 pages
• eBook: PDF Files
• Language: English
• ISBN-10: 3319625322
• ISBN-13: 978-3319625324
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Book Description

This book bridges the gap between playing with robots in school and studying robotics at the upper undergraduate and graduate levels to prepare for careers in industry and research. Robotic algorithms are presented formally, but using only mathematics known by high-school and first-year college students, such as calculus, matrices and probability. Concepts and algorithms are explained through detailed diagrams and calculations.

It presents an overview of different types of robots and the components used to build robots, but focuses on robotic algorithms: simple algorithms like odometry and feedback control, as well as algorithms for advanced topics like localization, mapping, image processing, machine learning and swarm robotics. These algorithms are demonstrated in simplified contexts that enable detailed computations to be performed and feasible activities to be posed. Students who study these simplified demonstrations will be well prepared for advanced study of robotics.

The algorithms are presented at a relatively abstract level, not tied to any specific robot. Instead a generic robot is defined that uses elements common to most educational robots: differential drive with two motors, proximity sensors and some method of displaying output to the user.

• Mordechai (Moti) Ben-Ari is with the Department of Science Teaching at the Weizmann Institute of Science. He has written many textbooks including Mathematical Surprises. Ben-Ari is a Distinguished Educator of the ACM and has received the ACM/SIGCSE Award for Outstanding Contributions to Computer Science Education.
• Francesco Mondada is with the Laboratory of Robotics Systems at the Ecole Polytechnique Fédérale de Lausanne (EPFL).

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• Robotics and Robot Programming
• Machine Learning
• Deep Learning and Neural Networks
• Artificial Intelligence
• Embedded Systems

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