Parallel PnP Robots (eBook)

This book discusses the parametric modeling, performance evaluation, design optimization and comparative study of the high-speed, parallel pick-and-place robots. It collects the modeling methodology, evaluation criteria and design guidelines for parallel PnP robots to provide a systematic analysis method for robotic developers. Furthermore, it gathers the research results previously scattered in many prestigious international journals and conference proceedings and methodically edits them and presents them in a unified form. The book is of interest to researchers, R&D engineers and graduate students in industrial parallel robotics who wish to learn the core principles, methods, algorithms, and applications.

Dr. Guanglei Wu received his PhD in mechanical engineering from Aalborg University, Denmark, 2013. He was granted an industrial project by Innovation Fund Denmark and worked as a postdoc fellow in Aalborg University from 2014 to 2016. He was a visiting scholar in the Research Institute in Communications and Cybernetics of Nantes (IRCCyN, the former LS2N) in 2012. Currently, he is an associate professor  in Dalian University of Technology. His research interests include conceptual design of robots, performance evaluation of parallel mechanisms, design optimization and industrial robots. He is the referee of a number of international journals and conferences in the fields of mechanisms and robots. 

---

This book discusses the parametric modeling, performance evaluation, design optimization and comparative study of the high-speed, parallel pick-and-place robots. It collects the modeling methodology, evaluation criteria and design guidelines for parallel PnP robots to provide a systematic analysis method for robotic developers. Furthermore, it gathers the research results previously scattered in many prestigious international journals and conference proceedings and methodically edits them and presents them in a unified form. The book is of interest to researchers, R&D engineers and graduate students in industrial parallel robotics who wish to learn the core principles, methods, algorithms, and applications.