scholarly journals Absolute Positioning Accuracy Improvement in an Industrial Robot

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4354 ◽  
Author(s):  
Yizhou Jiang ◽  
Liandong Yu ◽  
Huakun Jia ◽  
Huining Zhao ◽  
Haojie Xia

The absolute positioning accuracy of a robot is an important specification that determines its performance, but it is affected by several error sources. Typical calibration methods only consider kinematic errors and neglect complex non-kinematic errors, thus limiting the absolute positioning accuracy. To further improve the absolute positioning accuracy, we propose an artificial neural network optimized by the differential evolution algorithm. Specifically, the structure and parameters of the network are iteratively updated by differential evolution to improve both accuracy and efficiency. Then, the absolute positioning deviation caused by kinematic and non-kinematic errors is compensated using the trained network. To verify the performance of the proposed network, the simulations and experiments are conducted using a six-degree-of-freedom robot and a laser tracker. The robot average positioning accuracy improved from 0.8497 mm before calibration to 0.0490 mm. The results demonstrate the substantial improvement in the absolute positioning accuracy achieved by the proposed network on an industrial robot.

2021 ◽  
Vol 15 (5) ◽  
pp. 599-610
Author(s):  
Md. Moktadir Alam ◽  
◽  
Soichi Ibaraki ◽  
Koki Fukuda

In advanced industrial applications, like machining, the absolute positioning accuracy of a six-axis robot is indispensable. To improve the absolute positioning accuracy of an industrial robot, numerical compensation based on positioning error prediction by the Denavit and Hartenberg (D-H) model has been investigated extensively. The main objective of this study is to review the kinematic modeling theory for a six-axis industrial robot. In the form of a tutorial, this paper defines a local coordinate system based on the position and orientation of the rotary axis average lines, as well as the derivation of the kinematic model based on the coordinate transformation theory. Although the present model is equivalent to the classical D-H model, this study shows that a different kinematic model can be derived using a different definition of the local coordinate systems. Subsequently, an algorithm is presented to identify the error sources included in the kinematic model based on a set of measured end-effector positions. The identification of the classical D-H parameters indicates a practical engineering application of the kinematic model for improving a robot’s positioning accuracy. Furthermore, this paper presents an extension of the present model, including the angular positioning deviation of each rotary axis. The angular positioning deviation of each rotary axis is formed as a function of the axis’ command angles and the direction of its rotation to model the effect of the rotary axis backlash. The identification of the angular positioning deviation of each rotary axis and its numerical compensation are presented, along with their experimental demonstration. This paper provides an essential theoretical basis for the error source diagnosis and error compensation of a six-axis robot.


2019 ◽  
Vol 11 (12) ◽  
pp. 1465
Author(s):  
Deng ◽  
Zhang ◽  
Cai ◽  
Xu ◽  
Zhao ◽  
...  

In recent years, China has launched YaoGan-13 and GaoFen-3, high-resolution synthetic aperture radar (SAR) satellites that can acquire global high-resolution images. The absolute positioning accuracy of such satellites is important for mapping areas without ground reference points and for automated processing. However, satellites without geometric calibration have poor absolute positioning accuracy, greatly restricting their application (e.g., land resource surveys). Therefore, they cannot meet national demands for high-resolution SAR images with good geometric accuracy. Here, we propose a series of methods to improve the absolute positioning accuracy of YaoGan-13 and GaoFen-3, such as the multiple-image combined calibration strategy and geometric calibration model for a real continuously moving configuration, including consideration of atmospheric propagation delay. Using high-accuracy ground control data collected from different areas, the 2-D and 3-D absolute positioning accuracies of YaoGan-13 and GaoFen-3 were assessed after implementation of the improvement measures. Experimental results showed that, after calibration, the 2-D absolute positioning accuracy of YaoGan-13 and GaoFen-3 are improved from 43.86 m to 2.57 m and from 30.34 m to 4.29 m, respectively. In addition, the 3-D absolute positioning accuracies of YaoGan-13 in plane and elevation are 3.21 m and 2.22 m, respectively. Improving the absolute positioning accuracy of these satellites could broaden the scope of their potential applications in the future.


2020 ◽  
Vol 17 (2) ◽  
pp. 172988142092164
Author(s):  
Junde Qi ◽  
Bing Chen ◽  
Dinghua Zhang

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.


2019 ◽  
Vol 16 (5) ◽  
pp. 172988141988307 ◽  
Author(s):  
Yahui Gan ◽  
Jinjun Duan ◽  
Xianzhong Dai

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.


Author(s):  
Wang Zhenhua ◽  
Xu Hui ◽  
Chen Guodong ◽  
Sun Rongchuan ◽  
Lining Sun

Purpose – The purpose of this paper is to present a distance accuracy-based industrial robot kinematic calibration model. Nowadays, the repeatability of the industrial robot is high, while the absolute positioning accuracy and distance accuracy are low. Many factors affect the absolute positioning accuracy and distance accuracy, and the calibration method of the industrial robot is an important factor. When the traditional calibration methods are applied on the industrial robot, the accumulative error will be involved according to the transformation between the measurement coordinate and the robot base coordinate. Design/methodology/approach – In this manuscript, a distance accuracy-based industrial robot kinematic calibration model is proposed. First, a simplified kinematic model of the robot by using the modified Denavit–Hartenberg (MDH) method is introduced, then the proposed distance error-based calibration model is presented; the experiment is set up in the next section. Findings – The experimental results show that the proposed calibration model based on MDH and distance error can improve the distance accuracy and absolute position accuracy dramatically. Originality/value – The proposed calibration model based on MDH and distance error can improve the distance accuracy and absolute position accuracy dramatically.


2016 ◽  
Vol 14 (1) ◽  
pp. 172988141667769 ◽  
Author(s):  
Nguyen Ngoc Son ◽  
Ho Pham Huy Anh ◽  
Nguyen Thanh Nam

This article proposes a novel advanced differential evolution method which combines the differential evolution with the modified back-propagation algorithm. This new proposed approach is applied to train an adaptive enhanced neural model for approximating the inverse model of the industrial robot arm. Experimental results demonstrate that the proposed modeling procedure using the new identification approach obtains better convergence and more precision than the traditional back-propagation method or the lonely differential evolution approach. Furthermore, the inverse model of the industrial robot arm using the adaptive enhanced neural model performs outstanding results.


Sensor Review ◽  
2020 ◽  
Vol 40 (1) ◽  
pp. 71-80 ◽  
Author(s):  
Guoyang Wan ◽  
Fudong Li ◽  
Wenjun Zhu ◽  
Guofeng Wang

Purpose The positioning and grasping of large-size objects have always had problems of low positioning accuracy, slow grasping speed and high application cost compared with ordinary small parts tasks. This paper aims to propose and implement a binocular vision-guided grasping system for large-size object with industrial robot. Design/methodology/approach To guide the industrial robot to grasp the object with high position and pose accuracy, this study measures the pose of the object by extracting and reconstructing three non-collinear feature points on it. To improve the precision and the robustness of the pose measuring, a coarse-to-fine positioning strategy is proposed. First, a coarse but stable feature is chosen to locate the object in the image and provide initial regions for the fine features. Second, three circular holes are chosen to be the fine features whose centers are extracted with a robust ellipse fitting strategy and thus determine the precise pose and position of the object. Findings Experimental results show that the proposed system has achieved high robustness and high positioning accuracy of −1 mm and pose accuracy of −0.5 degree. Originality/value It is a high accuracy method that can be used for industrial robot vision-guided and grasp location.


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