This book offers a comprehensive reference guide for modeling humanoid robots using intelligent and fuzzy systems. It provides readers with the necessary intelligent and fuzzy tools for controlling humanoid robots by incomplete, vague, and imprecise information or insufficient data, where classical modeling approaches cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including fuzzy control, metaheuristic-based control, neutrosophic control, etc. To foster reader comprehension, all chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers, and postgraduate students pursuing research on humanoid robots. Moreover, by extending all the main aspects of humanoid robots to its intelligent and fuzzy counterparts, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas, and developments.
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This book offers a comprehensive reference guide for modeling humanoid robots using intelligent and fuzzy systems. Moreover, by extending all the main aspects of humanoid robots to its intelligent and fuzzy counterparts, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas, and developments.
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Introduction to Humanoid Robots & Fuzzy Sets.- Fuzzy Logic in Humanoid Biomechanics.- Humanoid Robots and Metaheuristics.- Humanoid Robotics and Fuzzy Control.- Humanoid Robots and Neutrosophic sets.
This book offers a comprehensive reference guide for modeling humanoid robots using intelligent and fuzzy systems. It provides readers with the necessary intelligent and fuzzy tools for controlling humanoid robots by incomplete, vague, and imprecise information or insufficient data, where classical modeling approaches cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including fuzzy control, metaheuristic-based control, neutrosophic control, etc. To foster reader comprehension, all chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers, and postgraduate students pursuing research on humanoid robots. Moreover, by extending all the main aspects of humanoid robots to its intelligent and fuzzy counterparts, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas, and developments.
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Covers a broad range of knowledge on fuzzy sets which has been increasingly used in control and automation engineering Presents the theory and applications of fuzzy sets to humanoid robots in a comprehensive handbook style Serves as both a handbook and a reference book for the postgraduate engineering students, especially control and automation engineering, industrial engineering, and electronic engineering student Discusses how intelligent control and automation techniques can bring solutions to humanoid robotic problems Includes both theoretical and practical knowledge
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Produktdetaljer
ISBN
9783030671624
Publisert
2021-04-05
Utgiver
Vendor
Springer Nature Switzerland AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet
Biographical note
Professor Cengiz Kahraman is a full professor of Industrial Engineering at Istanbul Technical University. His research areas are engineering economics, quality management, statistical decision making, multicriteria decision making, and fuzzy decision making. He published about 260 journal papers and 200 conference papers. He is the editor of many international books from Springer and the editorial board member in 20 international journals. He is the Editor-in Chief of Journal of Fuzzy Logic and Modeling in Engineering published by Bentham Science. He is also the chair of INFUS (Intelligent and Fuzzy Systems) conferences.Dr. Eda Bolturk received her BSc degree in Industrial Engineering from Istanbul Commerce University and her MSc degree in Industrial Engineering from Istanbul Technical University. She was a Ph.D. student at Politecnico di Milano in Energy Department in Italy between 2013 and 2014. She received her Ph.D. degree in Industrial Engineering from Istanbul Technical University on fuzzy decision making. Her research areas are fuzzy logic, decision making, forecasting and risk management. She published more than 50 papers in international journals and chapters in international books. She organized some international conferences on fuzzy logic.