| Surface painting is a process of coating paint or other colored liquids on the surface of objects or groovess,which is widely used in industrial production and daily life.At present,there are semi-automatic paint dispenser and full-automatic paint dispenser on the market.However,there are still some problems such as poor flexibility,high environmental requirements and low work efficiency.Therefore,a fully automated paint dispensing system which has fast processing speed and good accuracy will be designed.In this paper,Delta robot and machine vision are combined to apply in surface painting process.Machine vision is used to realize automatic positioning of products,and Delta robot has the advantages of high precision and high speed to improve processing efficiency.The main work of this paper is as follows:(1)The overall structure of the visual surface paint system is designed.The visual surface paint system consists of mechanical structure,visual positioning system,motion control system and paint valve system.Delta robot is designed and built as the mechanical structure of the surface paint system.The scheme design and hardware selection of visual positioning system,motion control system and paint valve system are also carried out.(2)A visual positioning system based on template matching algorithm is designed.Aiming at the characteristics of smooth surface and easy reflection of painting products,template matching algorithm and image edge detection algorithm are studied.The template matching algorithm is improved.The matching process is divided into rough matching and fine matching,which improves the matching speed and speeds up about 0.23 s.According to the fact that there are many objects to be processed at the same time,a multi template matching algorithm is developed.(3)The path planning algorithm suitable for visual surface paint system is studied.The ant colony algorithm is introduced into the path planning of visual surface paint system.The simulation platform is designed and made by C#,and the effect of traditional X/Y direction optimization algorithm,genetic algorithm and ant colony algorithm in path planning is compared through a large number of simulation experiments.The experimental results show that the optimal path length of ant colony algorithm is only 40% ~ 50% of the optimal path length in X / Y direction,and the operation time is shorter than that of genetic algorithm,so it is suitable for painting path planning.(4)Aiming at the error problem of Delta robot caused by assembly clearance and long running time,a method of measuring and compensating robot error with binocular vision system is proposed.An automatic focusing calibration device is designed and built to complete the focusing and calibration of binocular camera instead of human.The experimental results show that the accuracy of the robot's repetitive positioning after compensation is up to 30 ?m.(5)Software design and surface paint system test.The system software is designed with C language,including camera control module,template matching module,path planning module and serial communication module.The image positioning accuracy and continuous discharging of paint spot system are tested.The maximum position error of image positioning module is not more than 1 pixel,and the maximum angle error is not more than 0.1 °.The control method is improved to solve the problem of uneven paint discharge.In this paper,Delta robot is set up as the mechanical structure of the surface paint system and template matching localization algorithm is compiled to realize automatic painting.Through a self-developed trajectory measurement compensation system,the end of the robot terminal repeat positioning accuracy reached 30?m,positioning accuracy reached 50?m.The visual surface paint system can be used not only in traditional product coloring field,but also in customized processing field with increasing demand,such as food customization and gift customization.It has practical engineering application value. |
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