Optimization of structure parameters of palletizing robot based on genetic algorithm in medicine

YU Tianbiao, QIAO Mu, LI Ming

(School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China)

Abstract: Aiming at the problem of the narrow working space and the redundant arm length of the palletizing robot applied in pharmaceutical packaging production line, a new method combining the graphic method and analytic method was proposed to analyze and solve this problem. DH positive kinematics theorymodel of palletizing robot was built and the correctness of the model was verified, on the basis the actual working conditions were considered. Matlab genetic algorithm toolbox was used to complete multiobjective parameter optimization on the arms length and working space, and the optimal design variables conforming to the job requirement were obtained. Finally, through the SimMechanics modular, the model of palletizing robot was built and the workspace of palletizing robot was simulated. The results indicate that the obtained optimization design variables can meet the expected requirements of the job, the palletizing robots effective arm length is apparently shortened and its working space is apparently increased without cavity and has good working performance, simultaneously the theory basis is provided for the structural design and optimization of palletizing robot.

Key words: palletizing robot; genetic algorithm; multiobjective optimization; workspace