Malachy Eaton

eBook, PDF

Evolutionary Humanoid Robotics (eBook, PDF)

Beschreibung

This book examines how two distinct strands of research on autonomous robots, evolutionary robotics and humanoid robot research, are converging. The book will be valuable for researchers and postgraduate students working in the areas of evolutionary robotics and bio-inspired computing.

Technische Details

• Geräte: PC
• ohne Kopierschutz
• Größe: 4.16MB

Barrierefreiheit

• Text-to-Speech

Autor

Dr. Malachy Eaton is a lecturer and researcher in the Dept. of Computer Science and Information Systems of the University of Limerick, Ireland. His interests include evolutionary computing and humanoid robotics.

Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 144
• Erscheinungstermin: 2. Februar 2015
• Englisch
• ISBN-13: 9783662445990
• Artikelnr.: 43799240

Rezensionen

"[The book] sheds light at the intersection of evolutionary search and robotics, with a special focus on humanoid or human-like robots. It is a skill to hit the right spot between introducing newcomers to a concept while also informing researchers already in the field. [The author] manages to do just that by delivering a nice flowing, quick to read book. ... I can recommend this book to starting graduate students in the fields of computer science and/or robotics, or researchers looking to get started with evolutionary robotics. ... The book's gaze is on humanoid robotics and Eaton does a good job at defining the terminology ... describing the various graduations of distinction between evolutionary robotics and evolutionary humanoid robotics, thus leading the reader to a more fundamental understanding of the levels of humanoid robots. ... a well-written, thoroughly researched introduction ... a wonderful guide for finding relevant references in the field. I highly recommend it for young researchers starting out in the field of EHR [and] people interested in the general idea of evolving robotic systems, both for humanoids and non-humanoid robots." [Jürgen Leitner, Genetic Programming and Evolvable Machines, 2015, DOI 10.1007/s10710-015-9256-2]