Research On Visual Servo Control Of Manipulator

The application of mechanical arm in automatic production can improve industrial production efficiency,reduce product manufacturing cycle and decrease labor cost.With the development of robot technology,the research on robot arm has become one of the hottest topics.With the rapid development of the mechanical arm technology,it needs to meet more urgent industrial requirements,For example,the structure of the mechanical arm is more lightweight,the movement control of the mechanical arm is more flexible,and the function of each module is more intelligent to adapt to the changes of various complex environments.etc.So the study of mechanical arm robot technology has great practical value.In this paper,an improved algorithm is proposed to solve the problems of low accuracy and poor robustness of uncalibrated visual servo control of 6-d OF manipulator,low efficiency and unreasonable planning of manipulator trajectory planning,and a corresponding uncalibrated visual servo control platform was built to verify the proposed algorithm.Experimental results show that the proposed method improves the efficiency and operation stability of manipulator trajectory planning.The main research work is as follows:1.This paper introduces the kinematics knowledge of the manipulator.Firstly,the coordinate representation and pose transformation of the manipulator are described.Secondly,the camera imaging model is described.In addition,the D-H parameter method is used to establish the connecting rod coordinate system.Finally,the forward and inverse kinematics solutions of the manipulator are analyzed and verified.2.Aiming at the poor accuracy and stability of the uncalibrated visual servo control of the manipulator,a KF-GALSTM algorithm was proposed.This method uses the genetic optimized long and short term memory neural network to compensate for the errors caused by Kalman filter,so as to obtain the optimal value of jacobian matrix,and proved the performance of the improved algorithm on MATLAB.Experimental results show that the improved algorithm ensures the smooth operation of the manipulator,reduces the image characteristic error oscillation,and improves the robustness of the uncalibrated visual servo control system.3.Aiming at the problem of low efficiency and unreasonable planning of manipulator trajectory,an improved gray Wolf algorithm was proposed,Using chaotic mapping to initialize the population,combining gray Wolf algorithm with cuckoo search algorithm,On the basis of the quintic polynomial trajectory interpolation algorithm,the comprehensive optimization objective of "time-energy" is established,Finally,the MATLAB simulation experiment proves that the proposed algorithm has fast convergence speed,less time for trajectory planning and low energy consumption,and meets all the requirements that the angular velocity and angular acceleration of the manipulator are smooth and continuous,realizing the efficient and stable operation of the manipulator.4.The experimental platform of the visual servo control system of the manipulator was built,and the improved algorithm was tested based on the system.The proposed uncalibrated visual servo control algorithm has the advantages of fast convergence speed,small image characteristic error and oscillation,short planning time,less energy consumption and stable operation of the manipulator.Fig.[105] table [13] reference [82]...