Quantum Robotics | A Primer on Current Science and Future Perspectives

Alex Mitev (u. a.)

ISBN 10: 162705913X / ISBN 13: 9781627059138

Published by Morgan & Claypool Publishers, 2017

About this Item

Quantum Robotics | A Primer on Current Science and Future Perspectives | Alex Mitev (u. a.) | Taschenbuch | Kartoniert / Broschiert | Englisch | 2017 | Morgan & Claypool Publishers | EAN 9781627059138 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Seller Inventory # 108346315

Bibliographic Details

• Title: Quantum Robotics | A Primer on Current Science and Future Perspectives
• Publisher: Morgan & Claypool Publishers
• Publication Date: 2017
• Language: English
• ISBN 10: 162705913X
• ISBN 13: 9781627059138
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 191H x 8D millimeters 235 millimeters width by 191 millimeters height by 8 millimeters depth
• Weight: 295 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Quantum robotics is an emerging engineering and scientific research discipline that explores the application of quantum mechanics, quantum computing, quantum algorithms, and related fields to robotics. This work broadly surveys advances in our scientific understanding and engineering of quantum mechanisms and how these developments are expected to impact the technical capability for robots to sense, plan, learn, and act in a dynamic environment. It also discusses the new technological potential that quantum approaches may unlock for sensing and control, especially for exploring and manipulating quantum-scale environments. Finally, the work surveys the state of the art in current implementations, along with their benefits and limitations, and provides a roadmap for the future.

About the Author

Prateek Tandon is the founder of the Quantum Robotics Group. He obtained his Ph.D. from the Robotics Institute at Carnegie Mellon University and his B.S. in Computer Engineering, Computer Science from the University of Southern California. His Ph.D. dissertation focused on Bayesian methods for sensor fusion and extracting structure from multiple noisy data observations. Having previously written on optimizing many classical machine learning methods for robotic sensing, improving fault tolerance and runtime scalability, Prateek's research interests include exploring the new possibilities that quantum methods and quantum machine learning hold for robotic perception, learning, and planning.