Research On Low-energy Integration Optimization Of High Speed And Heavy Load Palletizing Robot

Palletizing robots can accurately and efficiently instead of humankind doing palletizing and handing operation and adapt to changes of tasks,therefore,have been widely applied in logistics operations.At the present,energy saving and green manufacturing are emphasized,besides work efficiency and load capacity of palletizing robots,energy consumption also has been the focus of attention.In this paper,MD1200-YJ palletizing robot is the study object,using low-energy as the major objective,from multiple aspect study for the low-energy integrated optimization problem of palletizing robot such as minimum energy consumption optimization of joints driving system,trajectory optimization and mechanical structure optimization.The main research included:Firstly,a multi-factor dynamic model is established based on Kane equation,Stribeck friction model and structure parameters of the balance spring cylinder and motion parameters,and energy consumption model of the palletizing robot is established based on the multi-factor dynamic model and joule's law.The correctness of the models is verified by experiment.Secondly,a Fourier series genetic algorithm direct optimization method is proposed,which uses Fourier series approximation method to construct the motion law,takes each coefficient of Fourier series as the optimization variable,takes the minimum energy consumption as the optimization objective,takes the starting and ending motion parameters of trajectory as the constraint conditions,and combines genetic algorithm to solve.Through simulation and experiment,the optimization results are compared with the 3-4-5 polynomial motion law widely used in engineering,and the results showed that the motion law obtained by the optimization method significantly reduced the energy consumption of joint system.For this problem which using direct optimization method is heavy calculation burden and poor practicality,two new improving optimization algorithms,which have the superiority inheritance,are present such as keeping term number fine optimization and increasing term number gradually.Through the comparative analysis of the results of the three optimization methods,two new optimization algorithms have obvious advantages in reducing energy consumption and improving the dynamic performance of palletizing robot.Among them,the comprehensive performance of Key=8 motion rule obtained by the gradually increasing term number optimization algorithm is better,therefore it is taken as the basic motion rule of the follow-up research.Thirdly,trajectory optimization problem which using low-energy consumption as main objective and taking into account dynamic property of palletizing robot in the end door type trajectory typical working condition is researched.In terms of selecting law of motion,based on 3-4-5 polynomial motion law,the operator space trajectory planning is carried out to construct the door type trajectory.Key critical path points that can realize likeness door type trajectory based on Key=8 motion law under the joint space trajectory planning are choiced.Comparing the energy consumption and dynamic performance of the robot under the two trajectory planning methods,the results show that the motion law of Key=8 has obvious advantages.In terms of optimization of motion law,a comprehensive evaluation index of comprehensive consideration energy consumption and jerk of joint is proposed based on the Key=8 motion law.The division time of trajectory are selected as optimization variables;selecting the total time permanent,nominal parameters of servo motors,position,velocity and acceleration in the start and end of the motion process as constraint conditions;using the Genetic Algorithm optimize law of motion.By comparison,the optimized Key=8 motion law has a significant effect on reducing energy consumption and improving dynamic performance of the robot.Finally,structure optimization design for the palletizing robot is researched.Firstly,based on static analysis which is the end of the palletizing robot is in four typical positions in the working space,the target parts for structural optimization are preliminarily selected.Based on finite element method and the Key=8 motion law of after optimization,by modal analysis,modal test,vibration response test,frequency response analysis and the static analysis taking into account dynamic factor to determine to use mass,the maximal stress,the maximal deformation and the natural frequency as the optimization objectives or the constraint conditions;approximation models of objective functions are established by the Box-Behnken design and the response surface methodology;to determine weighting factor of each optimization objectives,an analytic hierarchy process based on finite element analysis(FEA + AHP)method is put forward to improve the objectivity of comparison matrix;the multi-objective optimization mathematical model is established;the multi-objective optimization problems are solved by the NSGA-II algorithm and obtained optimization results,and contrastive analysis of optimized model and initial model to verify validity of this optimization design method.The mass parameters before and after the optimization are substituted into the multi-factor dynamic model and the energy consumption model.And the analysis shows that the energy consumption of joint is obviously reduced by structural optimization.In addition,spring structure parameters and installation location parameters of balancing spring cylinder are optimized,and mechanical work of shoulder joint is reduced significantly.