Visual Servoing Control Research For Dual-arm System

Along with the rapid development of computer technology,automation technology,machine vision technology,and artificial intelligence technology,robot technology has experienced a rapid growth as a whole of the above-mentioned various technologies,too,and plays a more and more important role in the following widely applied fields,such as industrial production,life service,scientific experiment,disaster relief,space Exploration,etc.Since single arm robot is limited by its environment and its own conditions,many tasks are difficult to complete.At the same time,people want the robot to be more anthropoid,and can work together safely and efficiently to complete the tasks.Just under such a background,the dual-arm robot cames into being,and it is combined to be a structure through an effective collaborative control mechanism to complete the tasks together rather than being simply aggregated.In order to enable the dual-ram robot to work in uncertain dynamic environment and enhance its adaptive ability,the dual-ram robot is equipped with visual sensor,i.e.,camera.The dual-arm robot is a complex multi-input and multi-output system with very strong time-varying,coupling,and non-linear characteristics.Meanwhile,the images of camera lose the depth information of the environment,and the interference is easily involved in the images because the imaging process is sensitive to noise.Therefore,in order to realize the control task in the image plane space and the internal force space,or the control task in the target object space and the internal force space,the visual servoing research for the dual-arm robot faces many difficulties and challenges.As a result,the selection of this topic is of great practical significance and theoretical value.The structure of this paper is as follows:the first chapter describes the relevant research background and research significance.The second chapter outlines the background knowledge needed to carry out the research work,including the kinematics and dynamics modeling of the dual-arm robot,camera model and fuzzy logic system.In the third chapter,the trajectory tracking control method based on adaptive estimation of camera parameters is studied.In the fourth chapter,the trajectory tracking control method based on adaptive kinematics and dynamic fuzzy approximation is studied.In the fifth chapter,the trajectory tracking control method based on visual speed observer is studied.In the sixth chapter,the position based trajectory tracking control method is studied.With respect to the dual arm robot system,this paper mainly studies how to implement the visual servo control task and the internal force control task of the target object.The main research contents are as follows:(1)Trajectory tracking control method based on adaptive estimation of camera parameters.In the presence of the unknown camera parameters,it is minimized that the error between the projections of the feature points in the image plane and the projections calculated with the adaptively estimated camera parameters and the known kinematics,subsequently the adaptive estimation of camera parameters is realized by combining with the Slotine-Li method.Then,the trajectory tracking control task of the projections of the feature points in the image plane is realized with the image-based visual servoing method.At the same time,the tracking control task of the internal force on the target object is realized using the position/force hybrid control method.(2)Trajectory tracking control method based on kinematic adaptation and dynamic fuzzy approximation.Considering the kinematic and dynamic uncertainties caused by the relative pose uncertainty between the target object and the end-effector,the cooperative control of the dual-arm robot in kinematics and dynamics is affected.In this paper,the kinematic adaptive method is used to solve the problem to map the velocities of the projections of the feature points from the image plane space to the joint space.At the same time,the fuzzy logic system is introduced to approximate the real dynamic characteristics of the dual-arm robot.Then,the image-based visual servo method is used to realize the trajectory tracking control task in the image plane.Simultaneously,the trajectory tracking control task in the internal froce space is realized by the position/force hybrid control method.(3)Trajectory tracking control method based on visual velocity observer.Visual velocity error is an important error in visual servoing control,and it has an important influence on the control precision.However,the imaging of the camera is a process of generating and processing the current signal,and can be easily disturbed by various kinds of noise.Therefore,the accuracy of the visual velocity is difficult to be ensured,since the visual velocity is obtained by differentially calculating the noise-induced image.So the visual velocity observer is introduced,and then the observed value is used in the control design.Next,the binocular vision trajectory tracking control task is realized by using the image-based visual servoing method.In the meantime,the trajectory tracking control task for the internal froce applied to the target object is realized using the position/force hybrid control method.(4)Image-based Cartesian space trajectory tracking control method.The traditional position-based visual servo method requires the knowledge of camera parameters and target geometric model,additionally,the target object may exceed the filed of view of camera during the process of control because the image space of the camera is not in the control loop.With respect to the above problems,this paper introduces the calibrated binocular vision system to map the trajectory tracking task from the target object space to the image plane space of the binocular vision system.Next,the control method studied in the above research content(2)is combined with to implement the mapped trajectory tracking control task in image plane.Based on the binocular vision model,it can be proven that the implmentation of the mapped task in the image plane implies the implmentation of the original trajectory tracking task in the target object space.Simultaneously,the position/force hybrid control method is used to realize the trajectory tracking control task in the internal force space.