首页|Study Data from Beijing Information Science and Technology University Update Und erstanding of Robotics (Accurate Kinematic Calibration of a Six-dof Serial Robot By Using Hybrid Models With Reduced Dimension and Minimized Linearization Error s)
Study Data from Beijing Information Science and Technology University Update Und erstanding of Robotics (Accurate Kinematic Calibration of a Six-dof Serial Robot By Using Hybrid Models With Reduced Dimension and Minimized Linearization Error s)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Robotics are presented i n a new report. According to news reporting from Beijing, People's Republic of C hina, by NewsRx journalists, research stated, "PurposeIn typical model-based cal ibration, linearization errors are derived inevitably, and non-negligible negati ve impact will be induced on the identification results if the rotational kinema tic errors are not small enough or the lengths of links are too long, which is c ommon in the industrial cases. Thus, an accurate two-step kinematic calibration method minimizing the linearization errors is presented for a six-DoF serial rob ot to improve the calibration negative impact of linearization on identification accuracy is minimized by rem oving the responsible linearized kinematic errors from the complete kinematic er ror model." Funders for this research include National Natural Science Foundation of China ( NSFC), National Natural Science Foundation of China (NSFC).
BeijingPeople's Republic of ChinaAsi aEmerging TechnologiesMachine LearningRobotRoboticsBeijing Information Science and Technology University
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