Biologically Inspired Series-Parallel Hybrid Robots: Design, Analysis, and Control

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· Elsevier
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eBook 정보

Biologically Inspired Series-Parallel Hybrid Robots: Design, Analysis and Control provides an extensive review of the state-of-the-art in series-parallel hybrid robots, covering all aspects of their mechatronic system design, modelling, and control. This book highlights the modular and distributed aspects of their mechanical, electronics, and software design, introducing various modern methods for modelling the kinematics and dynamics of complex robots. These methods are also introduced in the form of algorithms or pseudo-code which can be easily programmed with modern programming languages. Presenting case studies on various popular series-parallel hybrid robots which will inspire new robot developers, this book will be especially useful for academic and industrial researchers in this exciting field, as well as graduate-level students to bring them closer to the latest technology in mechanical design and control aspects of the area. - Introduces clear definitions for all relevant terms and the foundational theories - Provides in-depth kinematics of various parallel mechanisms typically used in the design of series-parallel hybrid robots - Presents holistic methods for solving kinematics, dynamics, trajectory generation, and control of series-parallel hybrid robots considering large number of holonomic constraints - Investigates case studies on the mechatronic system design of various series-parallel hybrid robots for practitioners in the field

저자 정보

Shivesh Kumar is an assistant professor at the Division of Dynamics, Department of Mechanics and Maritime Sciences, Chalmers University of Technology in Gothenburg, Sweden. He is also a visiting researcher at the Robotics Innovation Center, German Research Center for Artificial Intelligence in Bremen, Germany. He obtained his PhD degree from the faculty of Mathematics and Computer Science at the University of Bremen (2019). His research interests include kinematics, dynamics, and control of robots with applications in the fields of exoskeletons, humanoids, rehabilitation, and industrial automation.Andreas Mueller obtained diploma degrees in mathematics, electrical engineering, and mechanical engineering, and a PhD in mechanics. He received his Habilitation in mechanics and is currently professor and director of the Institute of Robotics at the Johannes Kepler University, Linz, Austria. His current research interests include holistic modelling, model-based and optimal control of mechatronic systems, redundant robotic systems, parallel kinematic machines, biomechanics, and computational dynamics.Frank Kirchner studied computer science and neurobiology at the University Bonn, where he received his PhD degree in computer science. He was senior scientist at the Gesellschaft für Mathematik und Datenverarbeitung (GMD) in Sankt Augustin, Germany, and a Senior Scientist at the Department for Electrical Engineering at Northeastern University in Boston, USA. Dr. Kirchner was first appointed adjunct and then tenure track assistant professor at the Northeastern University, and then as a full professor at the University of Bremen. Since December 2005, Dr. Kirchner has also been director of the Robotics Innovation Centre (RIC) in Bremen.

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