Motion Optimization Of Delta Parallel Robot Based On Visual Guidance

Delta parallel robot is a kind of industrial robot with less degree of freedom,because of its rapidity and accuracy,it is widely used in the processing of small or medium parts and chip manufacturing industries.However,during the sorting work of existing Delta parallel robot,the large workspace makes the structure stability lower,the unordered sorting makes the work inefficient.To overcome the weakness of the disadvantages of the Delta robot,trajectory optimization and multi-objective motion optimization are studied.The main contents of this paper are as follows:In this paper firstly,the kinematic characteristics of Delta parallel robot are analyzed,including forward and inverse position solution,structural analysis and the establishment of the robot coordinate system,and the geometric model is simplified.At the same time,the workspace of Delta parallel robot is analyzed,the robot Jacobian matrix is proposed,and the velocity and acceleration of the mechanism is analyzed.The simulation is performed to verify the effectiveness of the simplified model.Then,the visual guidance system is modeled,and the dynamic picking motion planning based on visual guidance system is carried out,including the calibration of camera coordinate system and machine coordinate system and an image deduplication algorithm.According to the real-time coordinates of the workpiece read by the visual guidance system,a single dynamic pickup motion planning is carried out.To solve the problem of rapidity and stability in the process of picking,a vision guided trajectory optimization model is proposed,which uses the shortest path and the smoothness of the mechanism as the optimization objectives.Particle swarm algorithm is used to optimize the grasping trajectory.The feasibility of trajectory optimization is verified by simulation.Finally,the experimental platform is set up to verify the optimization model,the workpiece is randomly distributed on the conveyor belt in two ways: normal distribution and average distribution,the results of the experiment show that the optimized grasp trajectory improves the grasping efficiency and effectively reduced the impact of the end of the mechanism.