Research On Optimal Path Of Parallel Robot In Cocoon Sorting

With the development of silkworm industry in China,the quality requirements for silk are also increasing year by year,and the bad silkworm cocoons in silkworm cocoons are the key factors affecting the quality of silk.The traditional silkworm cocoon sorting is basically done by manual selection,which is not only time-consuming and laborious,but also with the increase of the demand for silk in the market,the labor intensity of the workers increases,which leads to inefficiency and seriously affects the quality of silk.In order to solve these problems,this paper uses Delta parallel robot to sort bad silkworm cocoons,and based on the kinematics analysis of Delta parallel robots,mainly studies the spatial motion path trajectory planning and end effector of Delta parallel robot end effector.The sorting sequence is analyzed and studied in two aspects.The main research contents of this paper are as follows:1.The structure of the Delta parallel robot is analyzed.The kinematics is modeled by the structure of the Delta parallel robot,and the established model is simplified.At the same time,the forward and inverse kinematics analysis of the Delta parallel robot is derived,and the forward and reverse motions are derived respectively.Learning expressions,analyzing the selection problem of multiple active arms in the case of determining the end position.2.Compare the existing end effector and select the vacuum suction end effector to complete the task of grabbing the residual defect.Combined with the actual situation of grasping the bad cocoon,the end effector motion path is planned.Based on the spatial straight line and the space arc trajectory,the motion path trajectory of the end effector is planned,and the transition function is introduced to alleviate the dramatic change of the motion acceleration.The induced vibration uses the interpolation method to make the sorting trajectory smooth and accurate.In order to improve the gripping efficiency of the end effector,the door-shaped trajectory is changed to a half-door trajectory,and the hyperelliptic curve trajectory is used instead of the circular trajectory transition,which effectively reduces the trajectory path of the end effector,and uses the polynomial to correct the trapezoidal addition.The deceleration algorithm significantly reduces the residual vibration of the robot.The improved trajectory was simulated by MATLAB,and the change of the active arm angle corresponding to the motion trajectory of the end effector was simulated.The change of the rotation angle of the active arm was recorded.Through actual tests,it is proved that the improved half-gate trajectory effectively improves the sorting rate by using the polynomial modified trapezoidal acceleration/deceleration algorithm,and the robot catching success rate is increased to 97.95%.3.After analyzing the single sorting motion trajectory,the overall sorting path is planned,that is,the sorting sequence problem,which is transformed into a traveling salesman problem,and an improved genetic algorithm is proposed to optimize the sorting sequence,and random Comparing sorting with fixed longitudinal sorting,the optimized path average is 8.48% and 2.79% shorter than the traditional sorting.And in the actual cocoon sorting experiment test,the sorting efficiency and success rate have been significantly improved,which proves that the performance and sorting efficiency of the parallel robot are improved to some extent.