scholarly journals Kinematic Calibration of Industrial Robots Based on Distance Information Using a Hybrid Identification Method

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Guanbin Gao ◽  
Yuan Li ◽  
Fei Liu ◽  
Shichang Han
Keyword(s):  
Industrial Robot ◽  
Kinematic Model ◽  
Error Model ◽  
Industrial Robots ◽  
Kinematic Calibration ◽  
Kinematic Parameters ◽  
Distance Information ◽  
End Effector ◽  
Hybrid Identification ◽  
Identification Method

To improve the positioning accuracy of industrial robots and avoid using the coordinates of the end effector, a novel kinematic calibration method based on the distance information is proposed. The kinematic model of an industrial robot is established. The relationship between the moving distance of the end effector and the kinematic parameters is analyzed. Based on the results of the analysis and the kinematic model of the robot, the error model with displacements as the reference is built, which is linearized for the convenience of the following identification. The singular value decomposition (SVD) is used to eliminate the redundant parameters of the error model. To solve the problem that traditional optimization algorithms are easily affected by data noise in high dimension identification, a novel extended Kalman filter (EKF) and regularized particle filter (RPF) hybrid identification method is presented. EKF is used in the preidentification of the linearized error model. With the preidentification results as the initial parameters, RPF is used to identify the kinematic parameters of the linearized error model. Simulations are carried out to validate the effectiveness of the proposed method, which shows that the method can identify the error of the parameters and after compensation the accuracy of the robot is improved.

An improved minimal error model for the robotic kinematic calibration based on the POE formula

Robotica ◽  
2021 ◽  
pp. 1-20
Author(s):  
Ruiqing Luo ◽  
Wenbin Gao ◽  
Qi Huang ◽  
Yi Zhang
Keyword(s):  
Least Squares Method ◽  
Industrial Robot ◽  
Kinematic Model ◽  
Error Model ◽  
Coordinate Frame ◽  
Exponential Map ◽  
Kinematic Calibration ◽  
Minimal Error ◽  
Serial Robots ◽  
Calibration Algorithm

Summary The conventional product of exponentials $\left(\rm POE\right)$ -based methods dissatisfy the parametric minimality for the kinematic calibration of serial robots due to overlooking the magnitude and pitch constraints. Thus, the minimal kinematic model is presented to solve this problem, which can be developed further. This paper puts forward an improved algorithm for the minimal parameter calibration. An actual kinematic model with the minimal parameters $\left(\rm MP\right)$ is constructed according to the geometric properties of actual joint twists in the auxiliary frames established on the basis of the nominal joint axes. Then, the initial pose error is defined in the tool coordinate frame, which is expressed as the exponential map of the twist, and all twist descriptions are unified, so as to give a unified kinematic model in mathematics. By differentiating the kinematic model, a minimal error model is derived in explicit form. Subsequently, we propose a novel parameter identification method, which identifies the orientation error and position error parameters separately by the iterative least-squares method and updates the MP uniformly. Finally, the simulations and experiments on the different serial robots are conducted to verify the correctness and effectiveness of the proposed algorithm. The simulation results show our calibration algorithm outperforms the existing ones in the accuracy aspect, and the experiment result shows that the absolute pose accuracy of the UR5 industrial robot is upgraded about 9 times under a statistics sense after the calibration.

scholarly journals Research of Calibration Method for Industrial Robot Based on Error Model of Position

2021 ◽  
Vol 11 (3) ◽  
pp. 1287
Author(s):  
Tianyan Chen ◽  
Jinsong Lin ◽  
Deyu Wu ◽  
Haibin Wu
Keyword(s):  
Coordinate System ◽  
Industrial Robot ◽  
Calibration Method ◽  
Error Model ◽  
Position Error ◽  
Industrial Robots ◽  
Positioning Error ◽  
Robot Position ◽  
General Measurement ◽  
Parameter Error

Based on the current situation of high precision and comparatively low APA (absolute positioning accuracy) in industrial robots, a calibration method to enhance the APA of industrial robots is proposed. In view of the "hidden" characteristics of the RBCS (robot base coordinate system) and the FCS (flange coordinate system) in the measurement process, a comparatively general measurement and calibration method of the RBCS and the FCS is proposed, and the source of the robot terminal position error is classified into three aspects: positioning error of industrial RBCS, kinematics parameter error of manipulator, and positioning error of industrial robot end FCS. The robot position error model is established, and the relation equation of the robot end position error and the industrial robot model parameter error is deduced. By solving the equation, the parameter error identification and the supplementary results are obtained, and the method of compensating the error by using the robot joint angle is realized. The Leica laser tracker is used to verify the calibration method on ABB IRB120 industrial robot. The experimental results show that the calibration method can effectively enhance the APA of the robot.

Finding Features of Positioning Error for Large Industrial Robots Based on Convolutional Neural Network

2021 ◽  
Author(s):  
Daiki Kato ◽  
Kenya Yoshitugu ◽  
Naoki Maeda ◽  
Toshiki Hirogaki ◽  
Eiichi Aoyama ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Production Systems ◽  
Industrial Robot ◽  
Three Dimensional ◽  
Industrial Robots ◽  
Numerical Control ◽  
Robot Motion ◽  
Positioning Error ◽  
End Effector

Abstract Most industrial robots are taught using the teaching playback method; therefore, they are unsuitable for use in variable production systems. Although offline teaching methods have been developed, they have not been practiced because of the low accuracy of the position and posture of the end-effector. Therefore, many studies have attempted to calibrate the position and posture but have not reached a practical level, as such methods consider the joint angle when the robot is stationary rather than the features during robot motion. Currently, it is easy to obtain servo information under numerical control operations owing to the Internet of Things technologies. In this study, we propose a method for obtaining servo information during robot motion and converting it into images to find features using a convolutional neural network (CNN). Herein, a large industrial robot was used. The three-dimensional coordinates of the end-effector were obtained using a laser tracker. The positioning error of the robot was accurately learned by the CNN. We extracted the features of the points where the positioning error was extremely large. By extracting the features of the X-axis positioning error using the CNN, the joint 1 current is a feature. This indicates that the vibration current in joint 1 is a factor in the X-axis positioning error.

A New Measurement Device for Kinematic Calibration of Parallel Manipulators

2004 ◽  
Author(s):  
Abdul Rauf ◽  
Sung-Gaun Kim ◽  
Jeha Ryu
Keyword(s):  
Parallel Manipulators ◽  
Measurement Procedure ◽  
Initial Guess ◽  
Measurement Noise ◽  
Kinematic Calibration ◽  
Kinematic Parameters ◽  
End Effector ◽  
Experimental Procedure ◽  
New Device ◽  
Rotation Component

Kinematic calibration is a process that estimates the actual values of geometric parameters to minimize the error in absolute positioning. Measuring all the components of Cartesian posture assure identification of all parameters. However, measuring all components, particularly the orientation, can be difficult and expensive. On the other hand, with partial pose measurements, experimental procedure is simpler. However, all parameters may not be identifiable. This paper proposes a new device that can be used to identify all kinematic parameters with partial pose measurements. Study is performed for a 6 DOF (degree-of-freedom) fully parallel Hexa Slide manipulator. The device, however, is general and can be used for other parallel manipulators. The proposed device consists of a link with U joints on both sides and is equipped with a rotary sensor and a biaxial inclinometer. When attached between the base and the mobile platform, the device restricts the end-effector’s motion to 5 DOF and measures two position components and one rotation component of the end-effector. Numerical analyses of the identification Jacobian reveal that all parameters are identifiable. Computer simulations show that the identification is robust for the errors in the initial guess and the measurement noise. Intrinsic inaccuracies of the device can significantly deteriorate the calibration results. A measurement procedure is proposed and cost functions are discussed to prevent propagation of the inaccuracies to the calibration results.

A new approach of kinematic geometry for error identification and compensation of industrial robots

2018 ◽  
Vol 233 (5) ◽  
pp. 1783-1794
Author(s):  
Zhi Wang ◽  
Huimin Dong ◽  
Shaoping Bai ◽  
Delun Wang
Keyword(s):  
Curve Fitting ◽  
Kinematic Model ◽  
Coordinate Measuring Machine ◽  
Reference Points ◽  
Industrial Robots ◽  
Kinematic Calibration ◽  
Kinematic Pair ◽  
Good Efficiency ◽  
New Approach ◽  
Measuring Machine

A new approach for kinematic calibration of industrial robots, including the kinematic pair errors and the link errors, is developed in this paper based on the kinematic invariants. In most methods of kinematic calibration, the geometric errors of the robots are considered in forms of variations of the link parameters, while the kinematic pairs are assumed ideal. Due to the errors of mating surfaces in kinematic pairs, the fixed and moving axes of revolute pairs, or the fixed and moving guidelines of prismatic pairs, are separated, which can be concisely identified as the kinematic pair errors and the link errors by means of the kinematic pair errors model, including the self-adaption fitting of a ruled surface, or the spherical image curve fitting and the striction curve fitting. The approach is applied to the kinematic calibration of a SCARA robot. The discrete motion of each kinematic pair in the robot is completely measured by a coordinate measuring machine. Based on the global kinematic properties of the measured motion, the fixed and moving axes, or guidelines, of the kinematic pairs are identified, which are invariants unrelated to the positions of the measured reference points. The kinematic model of the robot is set up using the identified axes and guidelines. The results validate the approach developed has good efficiency and accuracy.

Complete kinematic calibration of a 6-RRRPRR parallel kinematic machine based on the optimal measurement configurations

2019 ◽  
Vol 234 (1) ◽  
pp. 121-136 ◽  
Author(s):  
Chunyang Han ◽  
Yang Yu ◽  
Zhenbang Xu ◽  
Xiaoming Wang ◽  
Peng Yu ◽  
...  
Keyword(s):  
Kinematic Model ◽  
Inverse Kinematic ◽  
Error Model ◽  
Kinematic Calibration ◽  
Universal Joint ◽  
Parallel Kinematic Mechanism ◽  
Simulation And Experiment ◽  
Parallel Kinematic ◽  
Kinematic Mechanism ◽  
Selection Of

This paper presents a kinematic calibration of a 6-RRRPRR parallel kinematic mechanism with offset RR-joints that would be applied in space positioning field. In order to ensure highly accurate and highly effective calibration process, the complete error model, which contains offset universal joint errors, is established by differentiating inverse kinematic model. A calibration simulation comparison with non-complete error model shows that offset universal joint errors are crucial to improve the calibration accuracy. Using the error model, an optimal calibration configuration selection algorithm is developed to determine the least number of measurement configurations as well as the optimal selection of these configurations from the feasible configuration set. To verify the effectiveness of kinematic calibration, a simulation and experiment were performed. The results show that the developed approach can effectively improve accuracy of a parallel kinematic mechanism with relatively low number of calibration configurations.

scholarly journals Modular fastening system and tool–holder working unit for incremental forming

2019 ◽  
Vol 299 ◽  
pp. 05005
Author(s):  
Melania Tera ◽  
Claudia–Emilia Gîrjob ◽  
Cristina–Maria Biriș ◽  
Mihai Crenganiș
Keyword(s):  
Machine Tools ◽  
Incremental Forming ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Cnc Milling ◽  
End Effector ◽  
Tool Holder ◽  
Cnc Milling Machine ◽  
Milling Machines ◽  
Sheet Metal Workpiece

Incremental forming can be usually unfolded either on CNC milling machine–tools or serial industrial robots. The approach proposed in this paper tackles the problem of designing a modular fastening system, which can be adapted for both above mentioned technological equipment. The fastening system of the sheet–metal workpiece is composed of a fixing plate and a retaining plate. The fixing and retaining plates will be made up of different individual elements, which can be easily repositioned to obtain different sizes of the part. Moreover, the fastening system has to be able to be positioned either horizontally (to be fitted on CNC milling machines) or vertically (to be fitted on industrial robots. The paper also presents the design of a tool–holder working unit which will be fitted on KUKA KR 210 industrial robot. The working unit will be mounted as end–effector of the robot and will bear the punch, driving it on the processing toolpaths.

scholarly journals Online pose correction of an industrial robot using an optical coordinate measure machine system

2018 ◽  
Vol 15 (4) ◽  
pp. 172988141878791 ◽  
Author(s):  
Sepehr Gharaaty ◽  
Tingting Shu ◽  
Ahmed Joubair ◽  
Wen Fang Xie ◽  
Ilian A Bonev
Keyword(s):  
Root Mean Square ◽  
Spot Welding ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Mean Square ◽  
End Effector ◽  
Proportional Integral ◽  
Accuracy Requirement ◽  
Robot Controller ◽  
Correction Scheme

In this article, a dynamic pose correction scheme is proposed to enhance the pose accuracy of industrial robots. The dynamic pose correction scheme uses the dynamic pose measurements as feedback to accurately guide the robot end-effector to the desired pose. The pose is measured online with an optical coordinate measure machine, that is, C-Track 780 from Creaform. A root mean square method is proposed to filter the noise from the pose measurements. The dynamic pose correction scheme adopts proportional-integral-derivaitve controller and generates commands to the FANUC robot controller. The developed dynamic pose correction scheme has been tested on two industrial robots, FANUC LR Mate 200iC and FANUC M20iA. The experimental results on both robots demonstrate that the robots can reach the desired pose with an accuracy of ±0.050 mm for position and ±0.050° for orientation. As a result, the developed pose correction can make the industrial robots meet higher accuracy requirement in the applications such as riveting, drilling, and spot welding.

Industrial Robot Kinematics Parameter Identification

2014 ◽  
Vol 889-890 ◽  
pp. 1136-1143
Author(s):  
Yong Gui Zhang ◽  
Chen Rong Liu ◽  
Peng Liu
Keyword(s):  
Experimental Data ◽  
Genetic Algorithms ◽  
Parameter Identification ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Robot Kinematics ◽  
Kinematic Parameters ◽  
Unknown Parameters ◽  
Preliminary Measurement ◽  
Kinematics Modeling

For an industrial robots with unknown parameters, on the basis of preliminary measurement and data of the Cartesian and joints coordinates which are shown on the FlexPendant, the kinematic parameters is identified by using genetic algorithms and accurate kinematics modeling of the robot is established. Experimental data could prove the validity of this method.

Study of Neural-Kinematics Architectures for Model-Less Calibration of Industrial Robots

2021 ◽  
Vol 33 (1) ◽  
pp. 158-171
Author(s):  
Monica Tiboni ◽  
◽  
Giovanni Legnani ◽  
Nicola Pellegrini
Keyword(s):  
Degrees Of Freedom ◽  
Industrial Robot ◽  
Kinematic Model ◽  
Back Propagation ◽  
Simulated Data ◽  
Industrial Robots ◽  
Robot Calibration ◽  
Feed Forward Neural Network ◽  
Comparative Performance ◽  
Order Of Magnitude

Modeless industrial robot calibration plays an important role in the increasing employment of robots in industry. This approach allows to develop a procedure able to compensate the pose errors without complex parametric model. The paper presents a study aimed at comparing neural-kinematic (N-K) architectures for a modeless non-parametric robotic calibration. A multilayer perceptron feed-forward neural network, trained in a supervised manner with the back-propagation learning technique, is coupled in different modes with the ideal kinematic model of the robot. A comparative performance analysis of different neural-kinematic architectures was executed on a two degrees of freedom SCARA manipulator, for direct and inverse kinematics. Afterward the optimal schemes have been identified and further tested on a three degrees of freedom full SCARA robot and on a Stewart platform. The analysis on simulated data shows that the accuracy of the robot pose can be improved by an order of magnitude after compensation.

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