Guanbin Gao

Structural Parameter Identification for Articulated Arm Coordinate Measuring Machines

Errors of structural parameters are the most important factors causing uncertainty of articulated arm coordinate measuring machines (AACMMs). Therefore these parameters must be identified to insure the accuracy of AACMMs. The kinematic model of six degree of freedom (6-DOF) AACMMs was established, and the structural parameters influencing the accuracy of AACMMs were achieved through analysis. A method to acquire data for identification with a cone-shape hole was presented. With single-point repeatability as the objective function, a modified simulated annealing algorithm (MSAA) was presented to identify structural parameters. A 6-DOF AACMM was used to carry out experimental tests in order to evaluate the efficiency of the MSAA, showing that after identification the repeatability and length measuring accuracy are improved greatly.

Kinematic Calibration for Articulated Arm Coordinate Measuring Machines Base on Particle Swarm Optimization

Kinematic calibration is one of the most important ways to improve the accuracy of articulated arm coordinate measuring machines (AACMMs). The kinematic model of six degree of freedom (6-DOF) AACMMs was established by Denavit-Hartenberg method. One calibration technology base on particle swarm optimization (PSO) was presented, which used single-point repeatability as the fitness function and kinematic parameters as the position vector. An adaptive inertia weight was presented to improve the ability of global exploration and local exploitation of the PSO. A 6-DOF AACMM was used to carry out experimental tests in order to evaluate the efficiency of the self-calibration technology, showing that after calibration the accuracy is improved greatly.