Trajectory Planning Of Camellia Oleifera Flower Collection Robot Arm Based On Improved PSO Algorithm

Artificial pollination is an important technical way to improve the yield of Camellia oleifera flower,and the collection of Camellia oleifera flower is the prerequisite for extracting pollen.In view of the problems of high labor intensity and low efficiency in manual collection of camellia,a camellia collection robot was designed to lay a technical foundation for subsequent mechanized pollination.In this paper,the trajectory planning of camellia collection robotic arm will be carried out,and the main research work is as follows:(1)The coordinate system of the manipulator link is established,the kinematics model is obtained and the forward and reverse kinematics are solved to realize the conversion of the coordinates of the manipulator in Cartesian space and joint space.With the help of the robot toolbox,the forward and reverse kinematics are simulated and verified,and the end working space is simulated by simulation software,which verifies the rationality of the design of the robotic arm.(2 Analyze the advantages and disadvantages of joint space and Cartesian space trajectory planning,and determine the trajectory planning of Camellia oleifera flower collection robotic arm in joint space.)Different interpolation functions such as 3-3-3,5-5-5 piecewise polynomials and 3-5-3 mixed polynomials are simulated using MATLAB software.The simulation results show that the 3-5-3 hybrid polynomial has obvious advantages over the other two single interpolation algorithms,and is more suitable for the traj ectory planning of camellia collection manipulator.(3)An improved PSO algorithm is proposed,which optimizes and analyzes the trajectory of 3-5-3 hybrid polynomial construction with time fitness function,and completes the fitting of each joint motion trajectory in simulation software.The improved PSO algorithm is compared with the standard particle swarm algorithm and the changed learning factor particle swarm algorithm,and the results show that the improved PSO algorithm has fast convergence speed,fast search efficiency,and can achieve the expected optimization goal.(4)Build a motion control experimental platform and complete the design of hardware circuits and software;Carry out the end position error test of camellia collection manipulator and the performance test of manipulator collection.The position error test results show that the position error at the end of the robotic arm can be controlled within 5mm,which can achieve more accurate positioning work.The acquisition performance test results show that the robotic arm can reach the target acquisition position and complete the acquisition task according to the trajectory planned by the improved PSO algorithm.The improved PSO algorithm was compared with the trajectory planned by the standard particle swarm algorithm and the improved learning factor particle swarm algorithm,and the acquisition success rates were 89.1%,78.1%and 82.8%,and the average motion time was 3.75s,4.86s and 4.95s,respectively,which further verified the superiority of the improved PSO algorithm.This paper provides a good foundation for further research on the intelligence and practicality of camellia collection robots,and in the future work,in-depth research can be carried out from the aspects of optimizing the mechanical structure of robots and improving control accuracy.