A calibration method for enhancing robot accuracy through integration of kinematic model and spatial interpolation algorithm

2021 ◽  
pp. 1-27
Author(s):  
Junde Qi ◽  
Bing Chen ◽  
Dinghua Zhang
Keyword(s):  
Spatial Interpolation ◽  
Residual Error ◽  
Compensation Method ◽  
Industrial Robots ◽  
Interpolation Algorithm ◽  
Random Errors ◽  
Spatial Error ◽  
Positioning Accuracy ◽  
Absolute Positioning ◽  
The Impact

Abstract Industrial robots are finding their niche in the field of machining due to their advantages of high flexibility, good versatility and low cost. However, limited by the low absolute positioning accuracy, there are still huge obstacles in high precision machining processes such as grinding. Aiming at this problem, a compensation method combining analytical modeling for quantitative errors with spatial interpolation algorithm for random errors is proposed based on the full consideration of the source and characteristics of positioning errors. Firstly, as for the quantitative errors, namely geometric parameter and compliance error in this paper, a kinematics-based error model is constructed taking the coupling effect of errors into consideration. Then avoiding the impact of random errors, the extended Kalman filtering algorithm (EKF) is adopted to identify the error parameters. Secondly, based on the similarity principle of spatial error, spatial interpolation algorithm is used to model the residual error caused by temperature, gear clearance etc. Based on the spatial anisotropy characteristics of robot motion performance, an adaptive mesh division algorithm was proposed to balance the accuracy and efficiency of mesh division. Then, an inverse distance weighted interpolation algorithm considering the influence degree of different joints on the end position was established to improve the approximation accuracy of residual error. Finally, the rough-fine two-stage serial error compensation method was carried out. Experimental results show the mean absolute positioning accuracy is improved from 1.165 mm to 0.106 mm, which demonstrates the effectiveness of the method in this paper.

scholarly journals Compensation for absolute positioning error of industrial robot considering the optimized measurement space

2020 ◽  
Vol 17 (2) ◽  
pp. 172988142092164
Author(s):  
Junde Qi ◽  
Bing Chen ◽  
Dinghua Zhang
Keyword(s):  
Industrial Robot ◽  
Measurement Data ◽  
Joint Space ◽  
Industrial Robots ◽  
Positioning Error ◽  
Positioning Accuracy ◽  
Decoupling Method ◽  
Absolute Positioning ◽  
Motion Characteristics ◽  
High Flexibility

Industrial robots are getting widely applied due to their low use-cost and high flexibility. However, the low absolute positioning accuracy limits their expansion in the area of high-precision manufacturing. Aiming to improve the positioning accuracy, a compensation method for the positioning error is put forward in terms of the optimization of the experimental measurement space and accurate modelling of the positioning error. Firstly, the influence of robot kinematic performance on the measurement accuracy is analysed, and a quantitative index describing the performance is adopted. On this basis and combined with the joints motion characteristics, the optimized measurement space in joint space as well as Cartesian space is obtained respectively, which can provide accurate measurement data to the error model. Then the overall model of the positioning error is constructed based on modified Denavit–Hartenberg method, in which the geometric errors and compliance errors are considered comprehensively, and an error decoupling method between them is carried out based on the error-feature analyses. Experiments on the KUKA KR210 robot are carried out finally. The mean absolute positioning accuracy of the robot increases from 1.179 mm to 0.093 mm, which verifies the effectiveness of the compensation methodology in this article.

scholarly journals A calibration method of robot kinematic parameters by drawstring displacement sensor

2019 ◽  
Vol 16 (5) ◽  
pp. 172988141988307 ◽  
Author(s):  
Yahui Gan ◽  
Jinjun Duan ◽  
Xianzhong Dai
Keyword(s):  
Calibration Method ◽  
Industrial Robots ◽  
Displacement Sensor ◽  
Kinematic Parameters ◽  
Position Measurement ◽  
Positioning Accuracy ◽  
End Effector ◽  
Displacement Sensors ◽  
Absolute Positioning ◽  
The Absolute

Calibration of robot kinematic parameters can effectively improve the absolute positioning accuracy of the end-effector for industrial robots. This article proposes a calibration method for robot kinematic parameters based on the drawstring displacement sensor. Firstly, the kinematic error model for articulated robot is established. Based on such a model, the position measurement system consisting of four drawstring displacement sensors is used to measure the actual position of the robot end-effector. Then, the deviation of the kinematic parameters of the robot is identified by the least-squares method according to robot end-effector deviations. The Cartesian space compensation method is adopted to improve the absolute positioning accuracy of the robot end-effecter. By experiments on the EFORT ER3A robot, the absolute positioning accuracy of the robot is significantly improved after calibration, which shows the effectiveness of the proposed method.

Research on Absolute Positioning Error of Robot Based on Mapping Theory

2014 ◽  
Vol 494-495 ◽  
pp. 1156-1160
Author(s):  
Guan Hua Dong ◽  
Ying Yin ◽  
Xiao Bing Hu
Keyword(s):  
Industrial Robots ◽  
Positioning Error ◽  
Positioning Accuracy ◽  
Compensation Algorithm ◽  
Absolute Positioning ◽  
The Absolute ◽  
Mapping Theory

Joint-typical Industrial robots tend to have higher repetitive positioning accuracy and lower absolute positioning accuracy. In order to improve the absolute positioning accuracy of robots, this paper puts forward a compensation algorithm based on the mapping theory combining with the kinematics equation, which establish the connection between the space of off-line programming and teaching-programming, so as to approximate the repeat positioning accuracy. A experiment is implemented to confirm its correctness, and the result shows that the supposed method can improve the absolute positioning accuracy heavily, which the absolute positioning error reduces from 8.32mm to 1.08mm.

scholarly journals Positioning Error Compensation for Industrial Robots Based on Stiffness Modelling

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yingjie Li ◽  
Guanbin Gao ◽  
Fei Liu
Keyword(s):  
Error Compensation ◽  
Compensation Method ◽  
Industrial Robots ◽  
Radial Deformation ◽  
Positioning Error ◽  
Axial Deformation ◽  
Element Analysis ◽  
Positioning Accuracy ◽  
Positioning Errors ◽  
Deformation Error

Insufficient stiffness of industrial robots is a significant factor which affects its positioning accuracy. To improve the positioning accuracy, a novel positioning error compensation method based on the stiffness modelling is proposed in this paper. First, the positioning errors considering the end load and gravity of industrial robots due to stiffness are analyzed. Based on the results of analysis, it is found that the positioning errors can be described by two kinds of deformation errors at joints: the axial deformation error and the radial deformation error. Then, the axial deformation error is modelled by the differential relationship of kinematics equations. The model of radial deformation error is deduced through the recurrence method and rotation transformation between joints. Finally, these two models are transformed into a Cartesian coordinate system, and a positioning error compensation method based on these two models is presented. Simulations based on the finite element analysis are implemented to verify the positioning error compensation method. The results show that the suggested method can efficiently predict the positioning error according to the gravity and loads, so that the positioning accuracy of industrial robots can be improved with the proposed method.

scholarly journals An ANN-Based Precision Compensation Method for Industrial Manipulators via Optimization of Point Selection

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhirong Wang ◽  
Zhangwei Chen ◽  
Chentao Mao ◽  
Xiang Zhang
Keyword(s):  
Error Compensation ◽  
Random Sequence ◽  
Joint Stiffness ◽  
Compensation Method ◽  
Training Data ◽  
Point Selection ◽  
Positioning Accuracy ◽  
Absolute Positioning ◽  
Large Joint ◽  
Industrial Manipulators

Industrial manipulators are widely used in the manufacture of products due to their high flexibility and low costs. High absolute positioning accuracy is the key to guarantee the product quality, which is commonly improved through the error compensation technology. Due to the variety, complexity, and unpredictability of the error sources, the influence of the nongeometric errors on the absolute positioning accuracy of manipulators is uncertain. In result, the existing error compensation methods are difficult to obtain satisfying results, especially for manipulators with large joint flexibility that need to work in different task scenarios. In this paper, an artificial neural network- (ANN-) based precision compensation method via optimization of point selection is proposed, which deals with the kinematic errors and joint stiffness errors in different task scenarios. Firstly, the quasi-random sequence (QRS) method and the product of exponentials (POE) model are combined to identify and compensate the geometric parameters. The QRS method can select points evenly in the workspace. And the POE model can avoid the singularity problem of Denavit–Hartenberg (DH) model. Secondly, a continuous joint stiffness compensation model in the whole workspace is established through ANN. In order to get better compensation results for the current task scenario, the point selection method based on trajectory similarity is adopted to determine the training data of ANN. Finally, the experiments are conducted on a 6-DOF industrial manipulator to demonstrate the validity of the proposed method. The results show that the ANN-based method via optimization of point selection could be an effective solution for the precision compensation.

scholarly journals Impact of Carbohydrate Counting Error on Glycemic Control in Open-Loop Management of Type 1 Diabetes: Quantitative Assessment Through an in silico Trial

2021 ◽  
pp. 193229682110123
Author(s):  
Chiara Roversi ◽  
Martina Vettoretti ◽  
Simone Del Favero ◽  
Andrea Facchinetti ◽  
Pratik Choudhary ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
In Silico ◽  
Open Loop ◽  
Random Errors ◽  
Linear Regression Models ◽  
Reference Case ◽  
Counting Error ◽  
The Impact

Background: In the management of type 1 diabetes (T1D), systematic and random errors in carb-counting can have an adverse effect on glycemic control. In this study, we performed an in silico trial aiming at quantifying the impact of different levels of carb-counting error on glycemic control. Methods: The T1D patient decision simulator was used to simulate 7-day glycemic profiles of 100 adults using open-loop therapy. The simulation was repeated for different values of systematic and random carb-counting errors, generated with Gaussian distribution varying the error mean from -10% to +10% and standard deviation (SD) from 0% to 50%. The effect of the error was evaluated by computing the difference of time inside (∆TIR), above (∆TAR) and below (∆TBR) the target glycemic range (70-180mg/dl) compared to the reference case, that is, absence of error. Finally, 3 linear regression models were developed to mathematically describe how error mean and SD variations result in ∆TIR, ∆TAR, and ∆TBR changes. Results: Random errors globally deteriorate the glycemic control; systematic underestimations lead to, on average, up to 5.2% more TAR than the reference case, while systematic overestimation results in up to 0.8% more TBR. The different time in range metrics were linearly related with error mean and SD ( R2>0.95), with slopes of [Formula: see text], [Formula: see text] for ∆TIR, [Formula: see text], [Formula: see text] for ∆TAR, and [Formula: see text], [Formula: see text] for ∆TBR. Conclusions: The quantification of carb-counting error impact performed in this work may be useful understanding causes of glycemic variability and the impact of possible therapy adjustments or behavior changes in different glucose metrics.

scholarly journals Characterization of Carrier Phase-Based Positioning in Real-World Jamming Conditions

2021 ◽  
Vol 13 (14) ◽  
pp. 2680
Author(s):  
Søren Skaarup Larsen ◽  
Anna B. O. Jensen ◽  
Daniel H. Olesen
Keyword(s):  
Real World ◽  
Carrier Phase ◽  
Reference Station ◽  
Baseline Length ◽  
Dual Frequency ◽  
Positioning Accuracy ◽  
The Impact ◽  
Single Versus ◽  
Selection Of

GNSS signals arriving at receivers at the surface of the Earth are weak and easily susceptible to interference and jamming. In this paper, the impact of jamming on the reference station in carrier phase-based relative baseline solutions is examined. Several scenarios are investigated in order to assess the robustness of carrier phase-based positioning towards jamming. Among others, these scenarios include a varying baseline length, the use of single- versus dual-frequency observations, and the inclusion of the Galileo and GLONASS constellations to a GPS only solution. The investigations are based on observations recorded at physical reference stations in the Danish TAPAS network during actual jamming incidents, in order to realistically evaluate the impact of real-world jamming on carrier phase-based positioning accuracy. The analyses performed show that, while there are benefits of using observations from several frequencies and constellations in positioning solutions, special care must be taken in solution processing. The selection of which GNSS constellations and observations to include, as well as when they are included, is essential, as blindly adding more jamming-affected observations may lead to worse positioning accuracy.

scholarly journals The Effect of BDS-3 Time Group Delay and Differential Code Bias Corrections on Positioning

2020 ◽  
Vol 11 (1) ◽  
pp. 104
Author(s):  
Peipei Dai ◽  
Jianping Xing ◽  
Yulong Ge ◽  
Xuhai Yang ◽  
Weijin Qin ◽  
...  
Keyword(s):  
Group Delay ◽  
Assessment System ◽  
Convergence Time ◽  
Single Frequency ◽  
Positioning Accuracy ◽  
Differential Code Bias ◽  
Receiver Clock ◽  
Code Bias ◽  
Point Positioning ◽  
The Impact

The timing group delay parameter (TGD) or differential code bias parameter (DCB) is an important factor that affects the performance of GNSS basic services; therefore, TGD and DCB must be taken seriously. Moreover, the TGD parameter is modulated in the navigation message, taking into account the impact of TGD on the performance of the basic service. International GNSS Monitoring and Assessment System (iGMAS) provides the broadcast ephemeris with TGD parameter and the Chinese Academy of Science (CAS) provides DCB products. In this paper, the current available BDS-3 TGD and DCB parameters are firstly described in detail, and the relationship of TGD and DCB for BDS-3 is figured out. Then, correction models of BDS-3 TGD and DCB in standard point positioning (SPP) or precise point positioning (PPP) are given, which can be applied in various situations. For the effects of TGD and DCB in the SPP and PPP solution processes, all the signals from BDS-3 were researched, and the validity of TGD and DCB has been further verified. The experimental results show that the accuracy of B1I, B1C and B2a single-frequency SPP with TGD or DCB correction was improved by approximately 12–60%. TGD will not be considered for B3I single-frequency, because the broadcast satellite clock offset is based on the B3I as the reference signal. The positioning accuracy of B1I/B3I and B1C/B2a dual-frequency SPP showed that the improvement range for horizontal components is 60.2% to 74.4%, and the vertical components improved by about 50% after the modification of TGD and DCB. In addition, most of the uncorrected code biases are mostly absorbed into the receiver clock bias and other parameters for PPP, resulting in longer convergence time. The convergence time can be max increased by up to 50% when the DCB parameters are corrected. Consequently, the positioning accuracy can reach the centimeter level after convergence, but it is critical for PPP convergence time and receiver clock bias that the TGD and DCB correction be considered seriously.

Sign in / Sign up

Export Citation Format

Share Document