Stiffness Modeling of Parallel Robots
Description
The book focuses on the stiffness modeling of serial and parallel manipulators It presents fundamentals and enhancements for Virtual Joint Modelling (VJM), Matrix Structural Analysis (MSA) and Finite Element Analysis (FEA). The described techniques consider complex kinematics with numerous passive joints, different types of loadings, including essential loadings leading to critical changes in the manipulator configurations, linear and non-linear stiffness analysis, conventional and non-linear compliance error compensation and stiffness parameters estimation from virtual experiments.
Presented enhancement for the VJM integrates in the stiffness analysis external force/torque applied to the end-point, internal preloading in the joints, and auxiliary forces/torques applied to intermediate points. The proposed technique includes computing an equilibrium configuration corresponding to the external/internal loading and allows obtaining the full-scale non-linear force-deflection relation for any given workspace point. This enables the designer to evaluate critical forces that may provoke non-linear behaviours of the manipulators, such as sudden failure due to elastic instability (buckling). The presented enhancement to the MSA allows users to carry out stiffness analysis for serial underactuated structures and over-constrained ones with multiple closed loops.
To increase the model accuracy of the VJM and MSA techniques a dedicated FEA-based stiffness model parameters identification technique is introduced in the book. It is based on the virtual experiments in the CAD/CAE environment and allows the VJM and MSA to achieve accuracy comparable with FEA, but it essentially reduces the computational effort, eliminating repetitive re-meshing through the workspace. All considered stiffness modelling techniques, kinematic particularities and loading conditions are illustrated with practical examples and related analysis.
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Dr. Alexandr Klimchik received a Ph.D. in Mechanical engineering (robotics) from Ecole Central Nantes, France in 2011. Previously, he was a postdoc at IMT Atlantique, France. In 2015- 2022 he worked at Innopolis University (Russia) where he was the founder of the National Centre of Competence in Robotics and Mechatronics, Director of Robotics and Computer Vision Institute, established new bachelor's and master's programs in Robotics, oversaw national strategy development in Robotics and Sensors.
Dr. Klimchik research experience contains essential results in designing new robotic solutions, stiffness modelling, robot calibration, human-robot collaboration and External impact estimation. His research interests include the enhancement of robot modelling, the design new robotic solutions and their components for various applications, improving technological task performance due to advanced modelling and deep integration of robotic and task-related knowledge.
Anatol Pashkevich received his MSc degree in Electrical Engineering (1977) and PhD in Control and Robotics (1982), both from Minsk Radio Engineering Institute, Belarus. In 1997 he received the second doctoral degree DSc in Industrial Automation. Since 1987 till 2007 he served as a head of the Robotic Laboratory at Belarusian State University of Informatics and RadioElectronics. In 2008 he joined a French technical university "Ecole des Mines de Nantes" where he served as a head of Automation and Production Systems Department and head of Control, Robotics and Interaction group. Currently he is a Professor Emeritus at the Department of Automation, Production and Computer Science, Institute Mines-Telecom Atlantique, France. His research interests include robotics, manufacturing automation and computer-aided design. He is a Member of the TC Manufacturing Plant Control of IFAC.
Dr. Damien Chablat has obtained his PhD in Mechanical Engineering at the University of Nantes/Ecole Centrale de Nantes, France, in 1998. After finishing his PhD, Dr. Chablat has worked for one year at the famous Centre for Intelligent Machines within the McGill University, Canada with Prof. Jorge Angeles. He came back to France and started to work at the Centre National de la Recherche Scientifique (CNRS) in 1999. He became CNRS senior researcher in 2011 and works now in the ROMAS team (Robots and Machines for Manufacturing, Society and Services) at Laboratoire des Sciences du Numérique de Nantes.
Two important milestones in Damien Chablat's career took place in 2023: the first in February 2023 when he assumed the role of head of robotics action at the National Research Agency (ANR) and the second when he became scientific manager of the European project Athena within the Technical University of Cluj-Napoca, Romania.
His research interests include robotics, the design of parallel manipulators and human fatigue evaluation for industrial tasks as well as the design of devices for medical surgeries. Under his supervision, 22 PhD degrees have been awarded, while and he is currently leading other 6 PhD students within four different research projects. As an evidence of his exceptional research career, Damien Chablat is in the Stanford University Names World's Top 2%.
Dr. Chablat is highly visible on the national level and actively contributes to the international scientific community via his presence in the editorial boards of journals as IFToMM Mechanism and Machine Theory, ASME Journal of Mechanisms and Robotics, ASME Letters in Translational Robotics.
Damien Chablat has published over 300 papers, with more than 70 in high-ranking journals (Machine and Mechanism Theory, Journal of Mechanisms and Robotics, Journal of Mechanical Design, etc.). He also has over 8200 citations, and an H-index of 44 (Google Scholar) and 32 (Scopus).
Content
Introduction.- 1 Introduction to stiffness modelling of robotic manipulators.- 2 State of the art of manipulator stiffness modelling.- 3 Finite Element Analysis in manipulator stiffness modelling.- 4 Matrix Structural Analysis and its application in robotics.- 5 Virtual Joint Modeling: a trade-off between the complexity and accuracy.- 6 Non-linear stiffness models for robotic manipulators under the loading.- 7 Evaluation of manipulator stiffness model parameters.- 8 Stiffness modelling of typical manipulator linkages and their assemblies.- Conclusions.- References.