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Table of contents

  1. Front Matter
    Pages i-xvi
  2. Mordechai Ben-Ari, Francesco Mondada
    Pages 1-20 Open Access
  3. Mordechai Ben-Ari, Francesco Mondada
    Pages 21-37 Open Access
  4. Mordechai Ben-Ari, Francesco Mondada
    Pages 39-53 Open Access
  5. Mordechai Ben-Ari, Francesco Mondada
    Pages 55-61 Open Access
  6. Mordechai Ben-Ari, Francesco Mondada
    Pages 63-93 Open Access
  7. Mordechai Ben-Ari, Francesco Mondada
    Pages 95-109 Open Access
  8. Mordechai Ben-Ari, Francesco Mondada
    Pages 111-126 Open Access
  9. Mordechai Ben-Ari, Francesco Mondada
    Pages 127-139 Open Access
  10. Mordechai Ben-Ari, Francesco Mondada
    Pages 141-163 Open Access
  11. Mordechai Ben-Ari, Francesco Mondada
    Pages 165-178 Open Access
  12. Mordechai Ben-Ari, Francesco Mondada
    Pages 179-183 Open Access
  13. Mordechai Ben-Ari, Francesco Mondada
    Pages 185-201 Open Access
  14. Mordechai Ben-Ari, Francesco Mondada
    Pages 203-220 Open Access
  15. Mordechai Ben-Ari, Francesco Mondada
    Pages 221-250 Open Access
  16. Mordechai Ben-Ari, Francesco Mondada
    Pages 251-265 Open Access
  17. Mordechai Ben-Ari, Francesco Mondada
    Pages 267-291 Open Access
  18. Back Matter
    Pages 293-308

About this book

Introduction

This book is open access under a CC BY 4.0 license.

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.

Elements of Robotics 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 use.

The theory is supplemented with over 100 activities, most of which can be successfully implemented using inexpensive educational robots. Activities that require more computation can be programmed on a computer. Archives are available with suggested implementations for the Thymio robot and standalone programs in Python.

Keywords

robotics autonomous mobile robots robotics algorithms Braitenberg creatures autonomic decision making Open Access

Authors and affiliations

  • Mordechai Ben-Ari
    • 1
  • Francesco Mondada
    • 2
  1. 1.Department of Science TeachingWeizmann Institute of ScienceRehovotIsrael
  2. 2.Laboratoire de Systèmes RobotiquesEcole Polytechnique Fédérale de LausanneLausanneSwitzerland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-62533-1
  • Copyright Information The Editor(s) (if applicable) and The Author(s) 2018
  • License CC BY
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-62532-4
  • Online ISBN 978-3-319-62533-1
  • Buy this book on publisher's site