Parallel robots with SCARA（selective compliance assembly robot arm） motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parall...Parallel robots with SCARA（selective compliance assembly robot arm） motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parallelogram structures included by the robots as a link. As the established error model fails to reflect the error feature of the parallelogram structures, the effect of accuracy design and kinematic calibration based on the error model come to be undermined. An error modeling methodology is proposed to establish an error model of parallel robots with parallelogram structures. The error model can embody the geometric errors of all joints, including the joints of parallelogram structures. Thus it can contain more exhaustively the factors that reduce the accuracy of the robot. Based on the error model and some sensitivity indices defined in the sense of statistics, sensitivity analysis is carried out. Accordingly, some atlases are depicted to express each geometric error’s influence on the moving platform’s pose errors. From these atlases, the geometric errors that have greater impact on the accuracy of the moving platform are identified, and some sensitive areas where the pose errors of the moving platform are extremely sensitive to the geometric errors are also figured out. By taking into account the error factors which are generally neglected in all existing modeling methods, the proposed modeling method can thoroughly disclose the process of error transmission and enhance the efficacy of accuracy design and calibration.展开更多
This article investigates virtual reality (VR)-based teleoperation with robustness against modeling errors. VR technology is an effective way to overcome the large time delay during space robot teleoperation. However,...This article investigates virtual reality (VR)-based teleoperation with robustness against modeling errors. VR technology is an effective way to overcome the large time delay during space robot teleoperation. However, it depends highly on the accuracy of model. Model errors between the virtual and real environment exist inevitably. The existing way to deal with the problem is by means of either model matching or robot compliance control. As distinct from the existing methods, this article tries to combine m...展开更多
Existing errors in the structure and kinematic parameters of multi-legged walking robots,the motion trajectory of robot will diverge from the ideal sports requirements in movement.Since the existing error compensation...Existing errors in the structure and kinematic parameters of multi-legged walking robots,the motion trajectory of robot will diverge from the ideal sports requirements in movement.Since the existing error compensation is usually used for control compensation of manipulator arm,the error compensation of multi-legged robots has seldom been explored.In order to reduce the kinematic error of robots,a motion error compensation method based on the feedforward for multi-legged mobile robots is proposed to improve motion precision of a mobile robot.The locus error of a robot body is measured,when robot moves along a given track.Error of driven joint variables is obtained by error calculation model in terms of the locus error of robot body.Error value is used to compensate driven joint variables and modify control model of robot,which can drive the robots following control model modified.The model of the relation between robot＇s locus errors and kinematic variables errors is set up to achieve the kinematic error compensation.On the basis of the inverse kinematics of a multi-legged walking robot,the relation between error of the motion trajectory and driven joint variables of robots is discussed.Moreover,the equation set is obtained,which expresses relation among error of driven joint variables,structure parameters and error of robot＇s locus.Take MiniQuad as an example,when the robot MiniQuad moves following beeline tread,motion error compensation is studied.The actual locus errors of the robot body are measured before and after compensation in the test.According to the test,variations of the actual coordinate value of the robot centroid in x-direction and z-direction are reduced more than one time.The kinematic errors of robot body are reduced effectively by the use of the motion error compensation method based on the feedforward.展开更多
Odometry using incremental wheel encoder odometry suffers from the accumulation of kinematic sensors provides the relative robot pose estimation. However, the modeling errors of wheels as the robot＇s travel distance ...Odometry using incremental wheel encoder odometry suffers from the accumulation of kinematic sensors provides the relative robot pose estimation. However, the modeling errors of wheels as the robot＇s travel distance increases. Therefore, the systematic errors need to be calibrated. The University of Michigan Benchmark（UMBmark） method is a widely used calibration scheme of the systematic errors in two wheel differential mobile robots. In this paper, the accurate parameter estimation of systematic errors is proposed by extending the conventional method. The contributions of this paper can be summarized as two issues. The first contribution is to present new calibration equations that reduce the systematic odometry errors. The new equations were derived to overcome the limitation of conventional schemes. The second contribu tion is to propose the design guideline of the test track for calibration experiments. The calibration performance can be im proved by appropriate design of the test track. The simulations and experimental results show that the accurate parameter es timation can be implemented by the proposed method.展开更多
Serial robots are used to handle workpieces with large dimensions, and calibrating kinematic parameters is one of the most efficient ways to upgrade their accuracy. Many models are set up to investigate how many kinem...Serial robots are used to handle workpieces with large dimensions, and calibrating kinematic parameters is one of the most efficient ways to upgrade their accuracy. Many models are set up to investigate how many kinematic parameters can be identified to meet the minimal principle, but the base frame and the kinematic parameter are indistinctly calibrated in a one-step way. A two-step method of calibrating kinematic parameters is proposed to improve the accuracy of the robot＇s base frame and kinematic parameters. The forward kinematics described with respect to the measuring coordinate frame are established based on the product- of-exponential （POE） formula. In the first step the robot＇s base coordinate frame is calibrated by the unit quaternion form. The errors of both the robot＇s reference configuration and the base coordinate frame＇s pose are equivalently transformed to the zero-position errors of the robot＇s joints. The simplified model of the robot＇s positioning error is established in second-power explicit expressions. Then the identification model is finished by the least square method, requiring measuring position coordinates only. The complete subtasks of calibrating the robot＇ s 39 kinematic parameters are finished in the second step. It＇s proved by a group of calibration experiments that by the proposed two-step calibration method the average absolute accuracy of industrial robots is updated to 0.23 mm. This paper presents that the robot＇s base frame should be calibrated before its kinematic parameters in order to upgrade its absolute positioning accuracy.展开更多
A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation ...A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation results show that this method can drive the static tracking error to zero quickly and keep good robustness and adaptability at the same time. In addition, the algorithm is very easy to be implemented with low computational complexity.展开更多
基金Supported by National Natural Science Foundation of China(Grant No.51305222)National Key Scientific and Technological Program of China(Grant No.2013ZX04001-021)
文摘Parallel robots with SCARA（selective compliance assembly robot arm） motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parallelogram structures included by the robots as a link. As the established error model fails to reflect the error feature of the parallelogram structures, the effect of accuracy design and kinematic calibration based on the error model come to be undermined. An error modeling methodology is proposed to establish an error model of parallel robots with parallelogram structures. The error model can embody the geometric errors of all joints, including the joints of parallelogram structures. Thus it can contain more exhaustively the factors that reduce the accuracy of the robot. Based on the error model and some sensitivity indices defined in the sense of statistics, sensitivity analysis is carried out. Accordingly, some atlases are depicted to express each geometric error’s influence on the moving platform’s pose errors. From these atlases, the geometric errors that have greater impact on the accuracy of the moving platform are identified, and some sensitive areas where the pose errors of the moving platform are extremely sensitive to the geometric errors are also figured out. By taking into account the error factors which are generally neglected in all existing modeling methods, the proposed modeling method can thoroughly disclose the process of error transmission and enhance the efficacy of accuracy design and calibration.
基金National Natural Science Foundation of China (60675054)National High-Tech Research and Development Program (2006AA04Z228)"111" Project (B07018)
文摘This article investigates virtual reality (VR)-based teleoperation with robustness against modeling errors. VR technology is an effective way to overcome the large time delay during space robot teleoperation. However, it depends highly on the accuracy of model. Model errors between the virtual and real environment exist inevitably. The existing way to deal with the problem is by means of either model matching or robot compliance control. As distinct from the existing methods, this article tries to combine m...
基金supported by National Natural Science Foundation of China (Grant Nos. 50675079,50875246)Program for Innovative Research Team (in Science and Technology) in University of Henan Province,China
文摘Existing errors in the structure and kinematic parameters of multi-legged walking robots,the motion trajectory of robot will diverge from the ideal sports requirements in movement.Since the existing error compensation is usually used for control compensation of manipulator arm,the error compensation of multi-legged robots has seldom been explored.In order to reduce the kinematic error of robots,a motion error compensation method based on the feedforward for multi-legged mobile robots is proposed to improve motion precision of a mobile robot.The locus error of a robot body is measured,when robot moves along a given track.Error of driven joint variables is obtained by error calculation model in terms of the locus error of robot body.Error value is used to compensate driven joint variables and modify control model of robot,which can drive the robots following control model modified.The model of the relation between robot＇s locus errors and kinematic variables errors is set up to achieve the kinematic error compensation.On the basis of the inverse kinematics of a multi-legged walking robot,the relation between error of the motion trajectory and driven joint variables of robots is discussed.Moreover,the equation set is obtained,which expresses relation among error of driven joint variables,structure parameters and error of robot＇s locus.Take MiniQuad as an example,when the robot MiniQuad moves following beeline tread,motion error compensation is studied.The actual locus errors of the robot body are measured before and after compensation in the test.According to the test,variations of the actual coordinate value of the robot centroid in x-direction and z-direction are reduced more than one time.The kinematic errors of robot body are reduced effectively by the use of the motion error compensation method based on the feedforward.
基金The MKE(The Ministry of Knowledge Economy),Korea,under the ITRC(Infor mation Technology Research Center)support programsupervised by the NIPA(National ITIndustry Promotion Agency)(NIPA-2012-C1090-1221-0010)TheMKE,Korea,under the Human Resources Development Programfor Convergence Robot Specialists support programsu-pervised by the NIPA(NIPA-2012-H1502-12-1002)Basic Science Research Program through the NRF funded by the MEST(2011-0025980)and MEST(2012-0005487)
文摘Odometry using incremental wheel encoder odometry suffers from the accumulation of kinematic sensors provides the relative robot pose estimation. However, the modeling errors of wheels as the robot＇s travel distance increases. Therefore, the systematic errors need to be calibrated. The University of Michigan Benchmark（UMBmark） method is a widely used calibration scheme of the systematic errors in two wheel differential mobile robots. In this paper, the accurate parameter estimation of systematic errors is proposed by extending the conventional method. The contributions of this paper can be summarized as two issues. The first contribution is to present new calibration equations that reduce the systematic odometry errors. The new equations were derived to overcome the limitation of conventional schemes. The second contribu tion is to propose the design guideline of the test track for calibration experiments. The calibration performance can be im proved by appropriate design of the test track. The simulations and experimental results show that the accurate parameter es timation can be implemented by the proposed method.
基金Supported by State Key Lab of Digital Manufacturing Equipment & Technology(Grant No.DMETKF2015013)National Natural Science Foundation of China(Grant No.51305008)
文摘Serial robots are used to handle workpieces with large dimensions, and calibrating kinematic parameters is one of the most efficient ways to upgrade their accuracy. Many models are set up to investigate how many kinematic parameters can be identified to meet the minimal principle, but the base frame and the kinematic parameter are indistinctly calibrated in a one-step way. A two-step method of calibrating kinematic parameters is proposed to improve the accuracy of the robot＇s base frame and kinematic parameters. The forward kinematics described with respect to the measuring coordinate frame are established based on the product- of-exponential （POE） formula. In the first step the robot＇s base coordinate frame is calibrated by the unit quaternion form. The errors of both the robot＇s reference configuration and the base coordinate frame＇s pose are equivalently transformed to the zero-position errors of the robot＇s joints. The simplified model of the robot＇s positioning error is established in second-power explicit expressions. Then the identification model is finished by the least square method, requiring measuring position coordinates only. The complete subtasks of calibrating the robot＇ s 39 kinematic parameters are finished in the second step. It＇s proved by a group of calibration experiments that by the proposed two-step calibration method the average absolute accuracy of industrial robots is updated to 0.23 mm. This paper presents that the robot＇s base frame should be calibrated before its kinematic parameters in order to upgrade its absolute positioning accuracy.
基金This project was supported by the National Natural Science Foundation (No. 69875010).
文摘A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation results show that this method can drive the static tracking error to zero quickly and keep good robustness and adaptability at the same time. In addition, the algorithm is very easy to be implemented with low computational complexity.
