Yongbo Wang, Huapeng Wu, and Heikki Handroos
Error modelling, differential evolution, calibration, parameter identification, hybrid robot, accuracy
This paper focuses on the geometrical error modelling and pa- rameter identification of a 10 degree-of-freedom (DOF) redundant serial–parallel hybrid intersector welding/cutting robot (IWR). The proposed hybrid robot consists of a kinematically redundant 4-DOF serial mechanism to enlarge workspace and a 6-DOF Stewart parallel robot to improve the end-effector accuracy. Due to its redundant degrees of freedom and the serial–parallel structure, the traditional error modelling and identification methods which tailored for pure serial robot or pure parallel robot cannot be directly used. In this paper, a hybrid error modelling method for redundant serial–parallel hybrid robot is presented by combining both the traditional forward calibration and inverse calibration method. Furthermore, because of the high nonlinear and multi-modal characteristics of the derived hybrid error model, the traditional iterative linear least-square al- gorithm cannot be utilized to identify the error parameters. In this paper, an easy-to-use and powerful evolutionary global optimization algorithm named differential evolution (DE) is employed to search for a set of optimum combination of all error parameters in the error model to minimize the discrepancies of measured and pre- dicted leg lengths. Numerical simulation and analysis are conducted by generating random manufacturing and assembly errors within the real error parameter tolerance range. Meanwhile, different measurement poses of the end-effector and the corresponding joint displacements of the serial mechanism are also randomly generated in the workspace to simulate the real physical behaviours. The simulation results show that the DE-based parameter identification method is robust and reliable, and all of the preset errors can be successfully recovered. The simulation also shows that the hybrid calibration method can avoid the external pose measurement of the connecting point between serial and parallel mechanism, and the pose measurement of the end-effector of serial–parallel robot can satisfy the calibration purpose effectively.
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