Latest Papers

ASME Journal of Mechanisms and Robotics

  • Measurement Configuration Optimization and Kinematic Calibration of a Parallel Robot
    by Huang C, Xie F, Liu X, et al. on December 10, 2021 at 12:00 am

    AbstractThis paper presents the kinematic calibration of a four-degrees-of-freedom (4DOF) high-speed parallel robot. In order to improve the calibration effect by decreasing the influence of the unobservable disturbance variables introduced by error measurement, a measurement configuration optimization method is proposed. Configurations are iteratively selected inside the workspace by a searching algorithm, then the selection results are evaluated through an index associated with the condition number of the identification Jacobian matrix; finally, the number of optimized configurations is determined. Since the selection algorithm has been shown to be sensitive to local minima, a meta-heuristic method has been applied to decrease this sensibility. To verify the effectiveness of the algorithm and kinematic calibration, computation validations, pose error estimations, and experiments are performed. The results show that the identification accuracy and calibration effect can be significantly improved by using the optimized configurations.

Optimization of Translational Flexure Joints Using Corrugated Units Under Stress Constraints


When optimizing corrugated flexure (CF) joints, most approaches for calculating the maximum stress on the CF beam depend on finite element analysis (FEA). The current paper introduces the design optimization for joints using CF units under stress constraints. The stress state is solved; based on that, the maximum displacement under stress constraints is deduced. The natural frequency formula of the translational joint is further derived from the results of the stiffness matrix. The stage configurations corresponding to the maximum displacement are optimized by restricting the off-axis/axial stiffness ratio and natural frequency of the joint. The optimal results of different types are validated by FEA and experiments.
Read More
Journal of Mechanisms and Robotics Open Issues