Autonomous Robotics and Deep Learning

  • Vishnu Nath
  • Stephen E. Levinson

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Vishnu Nath, Stephen E. Levinson
    Pages 1-3
  3. Vishnu Nath, Stephen E. Levinson
    Pages 5-16
  4. Vishnu Nath, Stephen E. Levinson
    Pages 17-24
  5. Vishnu Nath, Stephen E. Levinson
    Pages 25-30
  6. Vishnu Nath, Stephen E. Levinson
    Pages 31-38
  7. Vishnu Nath, Stephen E. Levinson
    Pages 39-45
  8. Vishnu Nath, Stephen E. Levinson
    Pages 47-64
  9. Vishnu Nath, Stephen E. Levinson
    Pages 65-66

About this book


This Springer Brief examines the combination of computer vision techniques and machine learning algorithms necessary for humanoid robots to develop “true consciousness.” It illustrates the critical first step towards reaching “deep learning,” long considered the holy grail for machine learning scientists worldwide. Using the example of the iCub, a humanoid robot which learns to solve 3D mazes, the book explores the challenges to create a robot that can perceive its own surroundings. Rather than relying solely on human programming, the robot uses physical touch to develop a neural map of its environment and learns to change the environment for its own benefit. These techniques allow the iCub to accurately solve any maze, if a solution exists, within a few iterations. With clear analysis of the iCub experiments and its results, this Springer Brief is ideal for advanced level students, researchers and professionals focused on computer vision, AI and machine learning.


Autonomous robots Computer vision Deep learning Machine learning iCub

Authors and affiliations

  • Vishnu Nath
    • 1
  • Stephen E. Levinson
    • 2
  1. 1.SeattleUSA
  2. 2.University of Illinois at Urbana-ChampaignUrbanaUSA

Bibliographic information

  • DOI
  • Copyright Information The Author(s) 2014
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-05602-9
  • Online ISBN 978-3-319-05603-6
  • Series Print ISSN 2191-5768
  • Series Online ISSN 2191-5776
  • Buy this book on publisher's site
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