Error Modeling and Compensation for a 6-DOF Robotic Crusher Based on Genetic Algorithm

In this paper, an error model of position and orientation is derived and the errors of actuator lengths are optimized based on genetic algorithm. Firstly, the error model of position and orientation is achieved according to the kinematic analysis, and the influencing factors are quantitatively analyzed. Then, the comprehensive error of position and orientation are given which can be used in the whole crushing cycle. It contains variables of the generalized coordinates. Finally, numerical simulation is used to verify the effectiveness of the proposed approach. The results show that the optimization effect of genetic algorithm is obvious, and all errors are reduced.