Research On Grasping Strategy Of Sorting Manipulator

With the implementation of Made in China 2025,the intellectualization of industrial manufacturing has become the mainstream trend.The sorting manipulator plays an important role and its application is becoming more and more widespread.But at present,the automation level of many industrial sorting manipulators is generally not high and does not meet the requirements of intelligent sorting.Therefore,the introduction of machine vision system to assist the sorting manipulator to achieve target recognition and tracking to achieve the purpose of fast sorting operations,has a very important practical application value.In this paper,based on the ability of a six-axis manipulator to realize its autonomous perception of the surrounding environment,the sorting manipulator can recognize,track and grasp the moving object by using machine vision,and the grasping strategy of the sorting manipulator is mainly studied.The main contents are as follows:(1)Set up a manipulator experimental platform to meet the needs of industrial assembly line sorting,clear the functional requirements of the sorting system,design the overall scheme of the sorting manipulator,including the structure of the sorting manipulator,hardware selection and software design and other components of the system,and analyze the application scenarios.(2)The trajectory planning of the grasping path of the sorting manipulator is studied.The structure of the sorting manipulator is analyzed,the D-H parameter model is established,and the forward and inverse kinematics of the manipulator is solved,so as to study and analyze the planning method of the movement trajectory of the sorting manipulator in joint space.Finally,based on the existing experimental platform of the manipulator,kinematics simulation of the sorting manipulator model was carried out in MATLAB,and the trajectory planning of the grasping path of the sorting manipulator was realized.(3)The method of recognition,tracking and location of moving target is studied.Firstly,HSV color model,color histogram and back projection are introduced.Then,the target image is preprocessed,the target image is de-noised by filtering and binary method,and the target is identified and detected by HSV threshold segmentation method.Finally,the target tracking framework is studied,the principle of Mean Shift method is derived in detail,and the target tracking design based on the improved Mean Shift algorithm Cam Shift adaptive tracking algorithm is realized,which improves the object recognition accuracy and improves the visual capture function of the sorting manipulator.(4)Based on the study of grasping strategy of sorting manipulator,the function test of the whole system is realized on the basis of each subsystem.Through the communication between hardware and software,the system was tested on the conveyor belt target recognition,tracking and positioning,and the success rate of grasping the target items by the manipulator under the laboratory environment.Finally,the visual grasping function of the sorting manipulator was verified.This paper provides a target tracking grasping strategy for the industrial sorting manipulator,and its research conclusions have certain reference significance for the industrial sorting manipulator.