Research On Dual Robot Cooperative Control System Oriented To Micro-nano Operation

At present,Micro-Electro-Mechanical Systems(MEMS)is used in various industries widely.MEMS is a miniature system composed of different materials and structural components to achieve specific functions.With the continuous miniaturization and complexity of MEMS,researchers have begun to use automated micro-assembly systems to assemble high-precision micro-electromechanical devices.For the micro-assembly system,the clamping and handling of parts is a key step to realize the task of micro-assembly.This article studies the gripping and handling of micro-parts in a two-dimensional plane.Through controlling the coordinated operation of the two micro-manipulation robots,the parts to be assembled are placed in the specified position accurately,which lays a solid foundation for the next high-precision assembly.First of all,for the problem of tracking and positioning the actuators and parts of the micro-manipulation robot during the cooperative motion process,this article designs a visual positioning algorithm based on the semantic segmentation model.The algorithm can be divided into the following three parts: 1.Use the Seg Net segmentation model to segment the actuators and parts of the micro-manipulation robot from the complex image background;2.Process the results of the segmentation of the model to obtain the actuators and parts respectively Binarized image;3.Locate the position of the micro-manipulation robot actuator through the inflection point detection algorithm,use the first-order moment and second-order moment of the image to find the position and rotation angle of the part.Then,this article proposes a cooperative handling control strategy for micro-parts in a two-dimensional plane.The main contents are as follows: 1.Measure the Z-axis height of the micro-manipulation robot actuator relative to the bottom surface through the contact detection algorithm,keep the height of the two micro-manipulation robots in the Z-axis direction consistent to ensure that the parts will not roll over during the gripping and movement;2.Adjust the part posture by controlling the collaborative operation of the robot,calculate the gripping position of the master and slave micro-manipulation robot actuator in the image through the Harris corner detection algorithm;2.Adjust the posture of the part by controlling the collaborative operation of the robot,and calculate the gripping position of the master-slave micro-manipulation robot actuator in the image through the Harris corner detection algorithm;3.For the problems of the RRT algorithm,plan the movement trajectory of the part through improvement Artificial Potential Field Algorithm;4.Derive the differential kinematics equation of the dual-micmanipulation robot cooperative system,design the master-slave controller of the micro-manipulation robot,and realize the cooperative movement of the dual micmanipulation robot.Finally,analyze the experiment.During the experiment,test the segmentation effect of the semantic segmentation model.compare the positioning algorithm proposed in this article with the template matching algorithm to verify the effectiveness of the positioning algorithm based on the semantic segmentation model.evaluate the visual tracking capabilities of the master micro-manipulation robot and the slave micro-manipulation robot in real experimental scenarios.coordinate the movement of the multi-micro-manipulation robot through master-slave control to move the parts to the specified position.