首页|Researchers from Tsinghua University Report Recent Findings in Robotics (Elasto-geometrical Calibration of a Hybrid Mobile Robot Considering Gravity Deformation and Stiffness Parameter Errors)
Researchers from Tsinghua University Report Recent Findings in Robotics (Elasto-geometrical Calibration of a Hybrid Mobile Robot Considering Gravity Deformation and Stiffness Parameter Errors)
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NETL
NSTL
Elsevier
Data detailed on Robotics have been presented. According to news reporting out of Beijing, People’s Republic of China, by NewsRx editors, research stated, “Hybrid mobile robots, which combine the advantages of serial and parallel robots and have the ability to realize processing in situ, have considerable application potential in the field of processing and manufacturing. In this paper, a hybrid mobile robot used for wind turbine blade polishing is presented.” Financial supporters for this research include National Key R&D Program of China, National Natural Science Foundation of China (NSFC). Our news journalists obtained a quote from the research from Tsinghua University, “The robot combines an automated guided vehicle, a 2-DoF robotic arm, and a 3-RCU parallel module. To improve the accuracy, investigating the elasto-geometrical calibration of the robot is necessary. Considering that the 3-RCU parallel module has weak stiffness along the gravitational direction, the stiffness model was established to estimate the deformation caused by the gravity of the mobile platform, ball screws, and motors. Subsequently, a rigid-flexible coupling error model considering structural and stiffness parameter errors is established. Based on these, a parameter identification method for the simultaneous identification of structural and stiffness parameter errors is proposed herein. For the 2-DoF robotic arm with parallelogram mechanisms, an intuitive error model considering the posture error caused by the parallelogram mechanism errors is established. The regularized nonlinear least squares method was adopted for parameter identifica-tion. Thereafter, a compensation strategy for the hybrid mobile robot that comprehensively considers the pose errors of the 3-RCU parallel module and 2-DoF robotic arm is proposed. Finally, a verification experiment was performed on the prototype, and the results indicated that after elasto-geometrical calibration, the maximum/mean of the position and posture errors of the hybrid mobile robot decreased from 3.738 mm/2.573 mm to 0.109 mm/0.063 mm and 0.236 degrees/0.179 degrees to 0.030 degrees/0.013 degrees, respectively. Owing to the decrease in the robot pose errors, the quality of the polished surface was more uniform.”
BeijingPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotRobotRoboticsRobotsTsinghua University
NETL
NSTL
Elsevier
