| In an uncalibrated visual servoing system,the image Jacobian matrix is used to represent the mapping relationship between the changes of image features and the changes of robot pose.The image Jacobian matrix needs to be updated dynamically in the servo process and its value can be obtained by the calibration of the camera and the robot.But it is difficult to calibrate the system accurately in engineering.Therefore,on-line estimation of image Jacobian matrix has become a hot topic in the field of robot visual servoing.Uncalibrated visual servo does not need to calibrate system parameters,which makes its engineering application prospect broad and has important research significance.In this paper,two different techniques of intelligent search and Kalman filter are used to study the online estimation method of image Jacobian matrix in robot uncalibrated visual servoing.It mainly includes:(1)Aiming at the Jacobian online estimation problem in the uncalibrated visual servoing problem,an image Jacobian online estimation method based on particle swarm search algorithm is proposed.This method utilizes three known quantities of the robot in the servo iteration process:The objective function of the Jacobian matrix at the current time is constructed based on the Jacobian matrix at the previous time,joint Angle increment and image error at the current time.Then,the iterative estimation of the Jacobian matrix is transformed into the extremum optimization problem of the objective function,and the particle swarm search algorithm(PSO)is introduced to solve the extremum problem.Based on this,an intelligent search algorithm is used to estimate the image Jacobian matrix online.(2)In order to improve the tracking accuracy of traditional Kalman filter in online estimation of image Jacobian matrix,an online estimation method of image Jacobian matrix combining Broyden and Kalman filter is proposed.In this method,the elements of the image Jacobian matrix are taken as the state vectors of the system,and the Kalman filter is used to estimate the state vectors on line.At the same time,the Jacobian iteration of Broyden method is added into the process of Kalman algorithm iteration,so as to realize the online dynamic estimation.The accuracy of Kalman filter algorithm in Jacobian estimation is improved.(3)The experimental platform of robot visual servo system is built.Based on REBOT-V-6R industrial robot and MV-CE060-10 UC industrial camera,the experimental platform of robot visual servo system with hand-eye configuration is built.The software platform is developed by using C# language under Window environment.Software functions include: industrial camera image acquisition and processing,robot control,human-machine control interface and other modules.The PSO-based Jacobian estimation method proposed in this paper is tested and verified on this platform,and the experimental results verify the effectiveness of the proposed method. |
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