Trajectory Optimization And Application Of Wooden Door Based On Six-axis Robot

With the development of Industry 4.0,the use of industrial robots has become more and more extensive.In automated production lines,thanks to the production efficiency and product quality that its manual operations cannot exceed,industrial robots are increasingly used in the fields of machinery manufacturing,medical treatment,chemical industry,etc.Outstanding,an important step in entering the era of intelligent manufacturing.In the automated spray processing industry,the application of industrial robot technology has also become increasingly rapid.Using spraying robots instead of manual spraying can not only improve spraying efficiency and quality,but also avoid the damage to workers' health caused by paint during manual spraying.This topic is based on the wooden door automatic spraying project of a company in Foshan.It proposes a new spraying trajectory planning algorithm,which has greater progress compared with the traditional spraying planning scheme.Reduce the time it takes to spray the workpiece and improve the efficiency of the robot processing of the workpiece.And through the Yaskawa MH50-II robot as the application platform,through the Moto Sim EG-VRC offline simulation platform to compare and verify the optimization effect of the planning method,and check whether its feasibility meets the demand.The trajectory planning method can not only extend the operating life of the robot,realize continuous spraying,and reduce spraying time,thereby improving spraying efficiency and spraying quality.This study carried out the following work:1.According to the mechanical structure of Yaskawa MH50-II,establish the link parameter list of the robot,use the improved D-H parameter method to establish its kinematics model,and solve the conversion problem between the forward and reverse kinematics of the robot.2.Plan the speed and movement trajectory of the robot during the operation process,so that the robot can complete the spray trajectory through linear interpolation and circular interpolation.3.Model the sprayed workpiece,and propose an improved spraying trajectory for the sprayed workpiece,and compare it with before the improvement.4.Analyze the causes of defects in the paint film,and propose corresponding solutions to these defects.Through the analysis of spraying parameters and the use of machine learning methods,the spraying height is predicted.5.Through the offline simulation platform Moto Sim EG-VRC,verify the reachability of the spray trajectory and whether it collides,and compare the differences before and after optimization.