Research On Robot Uncalibrated Visual Servoing Key Technique

Recently,Robot technology has become one of the representative strategic technology in the high-tech field,which leads the fundamentally changes in production mode of traditional industry so as to have far-reaching influences on the development of humankind soeiety.During the rapid developing of machine vision and hardware, visual servoing system is the combination between visual information and robot control,that made robot have the intelligent switching capacity with the external environment. This is one of the main direction of developing of robot. It can be forecasted that the intelligent robot with sensewill be applied more and more extensively.Traditional robot visual servoing control techonique is based on calibrated technologies,so that the control precision of the servo system depends largely on the precision of calibration. However in practiee,a variety of reasons,limit the application of the visual servoing control method based on calibrated teclnologies to a great extent.Uncalibrated visual servoing has become a hotspot in the field of robot visual servoing control.Uncalibrated visual servoing means that vision control law is designed direetly by the system state error from image plane without pre- calibrating the Parameters of camera and robot,which controls the robot to make system error converge to a permissible region.The dissertation develop the studies of robot uncalibrated visual servoing control,which is still in primary original and exploring stage in the field of robot visual serving control and doesn't set up the uniform system info.The passage introduced the content of the research of uncalibrated visual servoing, key technologies and existing problems,introduce the feature-points extraction method and control method,moreover, the developing of uncalibrated visual servoing method and the main research content are summarized.The dissertation research on the algorithm of feature-points extraction.Fusion information of edge and area color, putting into effect of stable image segmentation,then center of interest object.The method ultilize character of wavelet multi-scale to edge detection.whatever traditional wavelet edge detection technique was adopted, threshold was needed to filter candidate edge points for edge detection. However, threshold was obtained through experience presently, the best result was received after"cut and trial method"had been used repeatly, in addition, single-threshold calculation method can not accomplish accurate edge detection by now. These shortcomings restrict application of wavelet edge detection technique in practice.Aim at this problem,algorithm of self-adaptive calculating double thresholds based on method of minimum interclass variance was proposed, and any parameter was not needed artificial setting.Fusion color of self-selection area based on segmentation information and information of edge detection algorithm, achieve better effect of segmentation,feature-points are precise extracted, jumping phenomenon of segmentation based on color is avoided,problem of can not idetify interest object by edge detection method is solved.An dynamic uncalibrated method for visual servoing lechnique is presented, The approach for estimation of mutiplicity residual is proposed Recently, most of uncalibrated visual servoing technique are only for static target and some for dynamic target but can not dismiss effect of mutiplicity residual. In this dissertation,The robot system is controlled using dynamic nonlinear least squares optimization technique to tracking moving target. Dynamic quasi-newton approach is used to estimate imagejacobian matrix. System is more stable using recursive least squaresalgorithm. The robot can track object by this algorithm.A dynamic uncalibrated algorithm for eye-in-hand visual servoing structure to track a moving target is proposed. For the change of composite image Jacobian with time is unavailable in visual servoing system now, this dissertation presents a method to estimate this change.Vision guided algorithm for tracking dynamic image is developed through minimizing nonlinear objective function.Finally, an uncalibrated visual servoing experimental system is setted.Several group of experimental data show every algorithm is of correct.