Overview
- First comprehensive study on energy management in self-reconfigurable modular robotic organisms
- Addresses for the first time the concept of self-sufficiency and artificial energy homeostasis in the context of a modular robotic organism
- Describes in details the development of a dynamic power management system with fault tolerant energy sharing
- Includes supplementary material: sn.pub/extras
Part of the book series: Adaptation, Learning, and Optimization (ALO, volume 17)
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Table of contents (6 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book describes how the principle of self-sufficiency can be applied to a reconfigurable modular robotic organism. It shows the design considerations for a novel REPLICATOR robotic platform, both hardware and software, featuring the behavioral characteristics of social insect colonies. Following a comprehensive overview of some of the bio-inspired techniques already available, and of the state-of-the-art in re-configurable modular robotic systems, the book presents a novel power management system with fault-tolerant energy sharing, as well as its implementation in the REPLICATOR robotic modules. In addition, the book discusses, for the first time, the concept of “artificial energy homeostasis” in the context of a modular robotic organism, and shows its verification on a custom-designed simulation framework in different dynamic power distribution and fault tolerance scenarios. This book offers an ideal reference guide for both hardware engineers and software developers involved in the design and implementation of autonomous robotic systems.
Authors and Affiliations
Bibliographic Information
Book Title: Self-Sufficiency of an Autonomous Reconfigurable Modular Robotic Organism
Authors: Raja Humza Qadir
Series Title: Adaptation, Learning, and Optimization
DOI: https://doi.org/10.1007/978-3-319-10289-4
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2015
Hardcover ISBN: 978-3-319-10288-7Published: 09 October 2014
Softcover ISBN: 978-3-319-38375-0Published: 11 September 2016
eBook ISBN: 978-3-319-10289-4Published: 25 September 2014
Series ISSN: 1867-4534
Series E-ISSN: 1867-4542
Edition Number: 1
Number of Pages: XV, 154
Number of Illustrations: 63 b/w illustrations, 16 illustrations in colour
Topics: Robotics and Automation, Complexity, Artificial Intelligence, Biomedical Engineering and Bioengineering