Parallel PnP Robots

This book provides the design and application of multiple control algorithms and motion planning to a family of parallel robots, which can be generalized to other robot counterparts. The book covers the fundamentals of dynamic models for control design, as well as a comparison of the control effects from the classical to advanced control algorithms step by step, which can help the researcher to understand the design procedure of control algorithms. It also includes different trajectory planning algorithms to ensure optimal robot performances. Furthermore, the research results previously scattered in many prestigious journals and conferences worldwide are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers, R&D engineers, and graduate students in industrial parallel robotics who wish to learn the core principles, methods, algorithms, and applications.

Collect prestigious methods and results for dynamic control of parallel robots Provide the design from fundamental to advanced control and trajectory planning algorithms Present the core principles, methods, algorithms, and applications

Autorentext

Dr. Guanglei Wu received his Ph.D. in robotics from Aalborg University, Denmark, in 2013, and worked as an industrial postdoc fellow at Aalborg University from 2014 to 2016. He was a visiting scholar at the Research Institute in Communications and Cybernetics of Nantes (IRCCyN, currently reorganized as Laboratory of Digital Sciences of Nantes-LS2N) in June-July 2012, at McGill University in Aug. 2015, and at Aarhus University in 2020. Currently, he is an associate professor in the School of Mechanical Engineering, Dalian University of Technology (DUT). His research interests include robotic technology, conceptual design and performance evaluation of robots, robot dynamics and control, and industrial robots and their applications.

He has published one monography by Springer, 9 Chinese patents, and over 80 peer-reviewed articles in international journals and conferences.

Inhalt

Prerequisites.- Introduction.- Equations of Motion of Parallel SCARA Robot.- Identification of Dynamic Parameters.- Model-based Torque Control.- PD based Torque Control.- Fuzzy Torque Feedforward Control.- Fuzzy Sliding Mode Control.- Open-loop based Control.- Iterative Learning Control Design.- Input Shaping Control.- Motion Planning.- PPO Test Trajectory Design.- Trajectory Planning by Polynomial Curve.- NURBS Curve based Trajectory Design.- Trajectory Synthesis with Four-order S-curve.