首页|Research Conducted at Hefei University of Technology Has Provided New Informatio n about Robotics (Modified Dynamic Movement Primitives: Robot Trajectory Plannin g and Force Control Under Curved Surface Constraints)
Research Conducted at Hefei University of Technology Has Provided New Informatio n about Robotics (Modified Dynamic Movement Primitives: Robot Trajectory Plannin g and Force Control Under Curved Surface Constraints)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in Robotic s. According to news reporting from Hefei,People's Republic of China,by NewsRx journalists,research stated,"Dynamic movement primitives (DMPs) have been wid ely applied in robot motion planning and control. However,in some special cases ,original discrete DMP fails to generalize proper trajectories." Financial supporters for this research include Key Research and Development Prog ram of Guangdong Province,National Key Research and Development of China,Guang dong Special Support Program. The news correspondents obtained a quote from the research from the Hefei Univer sity of Technology,"Moreover,it is difficult to produce trajectories on the cu rved surface. To solve the above problems,a modified DMP method is proposed for robot control by adding the scaling factor and force coupling term. First,the adjusted cosine similarity is defined to assess the similarity of the generalize d trajectory with respect to the demonstrated trajectory. By optimizing the simi larity,the trajectories can be generated in all situations. Next,by adding the force coupling term derived from adaptive admittance control to the transformat ion system of the original DMP,the controller achieves the force control abilit y. Then,the modified DMP-based robot control system is developed. The stability and convergence of the system are proved. Finally,the high precisions of the p roposed method are verified by simulations and experiments." According to the news reporters,the research concluded: "The method is signific ant for trajectory learning and generalization on the curved surface."
HefeiPeople's Republic of ChinaAsiaEmerging TechnologiesMachine LearningRobotRoboticsHefei University of T echnology
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