Cable-driven parallel robots(CDPRs) are categorized as a type of parallel manipulators. In CDPRs, flexible cables are used to take the place of rigid links. The particular property of cables provides CDPRs several adv...Cable-driven parallel robots(CDPRs) are categorized as a type of parallel manipulators. In CDPRs, flexible cables are used to take the place of rigid links. The particular property of cables provides CDPRs several advantages, including larger workspaces, higher payload-to-weight ratio and lower manufacturing costs rather than rigid-link robots. In this paper, the history of the development of CDPRs is introduced and several successful latest application cases of CDPRs are presented. The theory development of CDPRs is introduced focusing on design, performance analysis and control theory. Research on CDPRs gains wide attention and is highly motivated by the modern engineering demand for large load capacity and workspace. A number of exciting advances in CDPRs are summarized in this paper since it is proposed in the 1980 s, which points to a fruitful future both in theory and application. In order to meet the increasing requirements of robot in different areas, future steps foresee more in-depth research and extension applications of CDPRs including intelligent control, composite materials, integrated and reconfigurable design.展开更多
With the surge of big data applications and the worsening of the memory-wall problem,the memory system,instead of the computing unit,becomes the commonly recognized major concern of computing.However,this“memorycent...With the surge of big data applications and the worsening of the memory-wall problem,the memory system,instead of the computing unit,becomes the commonly recognized major concern of computing.However,this“memorycentric”common understanding has a humble beginning.More than three decades ago,the memory-bounded speedup model is the first model recognizing memory as the bound of computing and provided a general bound of speedup and a computing-memory trade-off formulation.The memory-bounded model was well received even by then.It was immediately introduced in several advanced computer architecture and parallel computing textbooks in the 1990’s as a must-know for scalable computing.These include Prof.Kai Hwang’s book“Scalable Parallel Computing”in which he introduced the memory-bounded speedup model as the Sun-Ni’s Law,parallel with the Amdahl’s Law and the Gustafson’s Law.Through the years,the impacts of this model have grown far beyond parallel processing and into the fundamental of computing.In this article,we revisit the memory-bounded speedup model and discuss its progress and impacts in depth to make a unique contribution to this special issue,to stimulate new solutions for big data applications,and to promote data-centric thinking and rethinking.展开更多
基金Supported by National Natural Science Foundation of China(Grant Nos.51605126,51575150,91748109)
文摘Cable-driven parallel robots(CDPRs) are categorized as a type of parallel manipulators. In CDPRs, flexible cables are used to take the place of rigid links. The particular property of cables provides CDPRs several advantages, including larger workspaces, higher payload-to-weight ratio and lower manufacturing costs rather than rigid-link robots. In this paper, the history of the development of CDPRs is introduced and several successful latest application cases of CDPRs are presented. The theory development of CDPRs is introduced focusing on design, performance analysis and control theory. Research on CDPRs gains wide attention and is highly motivated by the modern engineering demand for large load capacity and workspace. A number of exciting advances in CDPRs are summarized in this paper since it is proposed in the 1980 s, which points to a fruitful future both in theory and application. In order to meet the increasing requirements of robot in different areas, future steps foresee more in-depth research and extension applications of CDPRs including intelligent control, composite materials, integrated and reconfigurable design.
基金supported in part by the U.S.National Science Foundation under Grant Nos.CCF-2029014 and CCF-2008907.
文摘With the surge of big data applications and the worsening of the memory-wall problem,the memory system,instead of the computing unit,becomes the commonly recognized major concern of computing.However,this“memorycentric”common understanding has a humble beginning.More than three decades ago,the memory-bounded speedup model is the first model recognizing memory as the bound of computing and provided a general bound of speedup and a computing-memory trade-off formulation.The memory-bounded model was well received even by then.It was immediately introduced in several advanced computer architecture and parallel computing textbooks in the 1990’s as a must-know for scalable computing.These include Prof.Kai Hwang’s book“Scalable Parallel Computing”in which he introduced the memory-bounded speedup model as the Sun-Ni’s Law,parallel with the Amdahl’s Law and the Gustafson’s Law.Through the years,the impacts of this model have grown far beyond parallel processing and into the fundamental of computing.In this article,we revisit the memory-bounded speedup model and discuss its progress and impacts in depth to make a unique contribution to this special issue,to stimulate new solutions for big data applications,and to promote data-centric thinking and rethinking.
