首页|New Robotics Study Findings Recently Were Reported by Researchers at University of Science and Technology China (Optimal Reconfiguration Planning of a 3-dof Point-mass Cable-driven Parallel Robot)
New Robotics Study Findings Recently Were Reported by Researchers at University of Science and Technology China (Optimal Reconfiguration Planning of a 3-dof Point-mass Cable-driven Parallel Robot)
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Research findings on Robotics are discussed in a new report. According to news reporting from Hefei, People’s Republic of China, by NewsRx journalists, research stated, “Cable-driven parallel robots (CDPRs) have attracted much attention due to their advantages, such as large workspace and excellent load capacity. However, their adaptability to different tasks has been limited because of fixed configurations.” Funders for this research include National Natural Science Foundation of China (NSFC), Natural Science Foundation of Anhui Province, Anhui Science Fund for Distinguished Young Scholars, China Postdoctoral Science Foundation, State Key Laboratory of Robotics and Systems. The news correspondents obtained a quote from the research from the University of Science and Technology China, “To improve this, a novel three-DOF point-mass reconfigurable CDPR (RCDPR) has been 47 designed, and its configuration can be changed by adjusting the positions of multiple cable anchors. Since wrench feasible workspace (WFW) is an essential criterion that describes the configuration characteristics, an optimal reconfiguration planning method is proposed to schedule the sequence and number of all movable cable anchors for adjusting the WFW range. Based on a two-level optimization process, the method can realize static reconfiguration (SR) or dynamic reconfiguration (DR) of the RCDPR. If SR cannot provide the required WFW by finding a static optimal configuration, the WFW range will be dynamically adjusted by DR. Besides, the number of movable cable anchors is minimized in DR by applying L-1-norm optimization to the anchor velocity sequences.”
HefeiPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningRobotRoboticsUniversity of Science and Technology China
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