Trajectory Planning And Control Strategy Optimization Of DELTA Robot In Drug Sorting

In recent years,with the rapid development of China's economy and the continuous reduction of production costs,more and more production companies have begun to introduce intelligent robot sorting systems in production workshops.Among them,DELTA parallel sorting robot is widely used in food,medical,electronic production and other industries.In view of the actual demand for accurate picking of robots in the current sorting production line,it is of great significance for the study of trajectory planning and control strategies in the sorting process.According to the actual demand in the drug sorting line,this paper firstly analyzes the kinematics modeling process of the robot sorting drugs.On this basis,the robot sorting door type trajectory is rationally planned,and then the sorting control strategy is adopted.Detailed analysis and introduction of neural network algorithm to optimize it,and finally through the establishment of the sorting experimental platform for verification.This article starts with the following contents:(1)Through the background analysis of the topic selection,as well as the development history,current situation,development trend of robots at home and abroad,and the research on robot sorting trajectory planning and control strategy,the research content of this paper is proposed.(2)Firstly,according to the geometry of DELTA robot,the simplified mathematical model is derived.On this basis,the forward and inverse solutions of the robot's motion position are obtained.Through the detailed analysis of the changes of speed and acceleration during the sorting movement of the medicine,the motion space of the robot end mechanism is obtained.(3)Secondly,according to the movement process of the DELTA robot in the drug sorting line,combined with the trajectory planning method such as sinusoidal function,modified trapezoidal and PH curve,the simulation of the comparison shows that the picking track after the PH curve method is more stable,The sorting efficiency is significantly improved.Then the motion control of the robot sorting process is analyzed and studied.According to the distribution characteristics of the drugs in the sorting production line and the position prediction method of the target material,the neural network algorithm is introduced to optimize the sorting control strategy of the medicine to improve the sorting accuracy rate.(4)Finally,the DELTA robot sorting experiment platform was built.The results of the sorting experiment showed that the above-mentioned robot PH trajectory planning method and its sorting control strategy were correct and feasible,and the sorting accuracy rate reached 87%.