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 mechatronics system design. The book highlights the modular and distributed aspects in their mechanical, electronics, and software design, presenting case studies on various famous series-parallel hybrid robots which will inspire new robot developers. The book also introduces various modern methods for modeling 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 day programming languages.
- Assembles the appropriate literature of kinematics of various mechanisms used in robots
- Provides software tools to aid the development of robots
- Introduces clear definitions of all important terms as well as foundational theory and background information
- Provides in-depth kinematic analysis of various parallel mechanisms that are typically used in the design of series-parallel hybrid robots
Part 1: Introduction to Biologically Inspired Hybrid Robots1. Motivation2. Modular and Decentralized Design PrinciplesPart 2: Geometric Analysis3. Modern methods in Geometric Analysis (4 bar mechanism, slider crank)4. Study of 2-DOF Parallel Mechanisms (2SPRR+1U, 2SPU+1U)5. Study of 3-DOF Parallel Mechanisms (Active Ankle)6. Study of 6-DOF Parallel Mechanisms (6-UPS, 6-RUS)Part 3: Kinematics, Dynamics and Control7. Kinematics and Dynamics of Tree-Type systems8. Modular Algorithms for Kinematics and Dynamics of series-parallel hybrid robots9. Learning and Control approaches for hybrid robotsPart 4: Mechatronic System Design of Some Hybrid Robots10. Hominid robot Charlie11. Multi-legged robot Mantis12. Active Suspension Rover: SherpaTT13. Recupera-Reha Exoskeleton14. RH5 Humanoid15. Lola humanoid16. NASA ValkyriePart 5: Outlook17. Parallel redundant mechanisms18. Soft actuation modules19. Computational Design of Hybrid Robots20. Conclusion and Future Work
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.
