A robot with improved absolute positioning accuracy for CT guided stereotactic brain surgery

1988 ◽  
Vol 35 (2) ◽  
pp. 153-160 ◽  
Author(s):  
Y.S. Kwoh ◽  
J. Hou ◽  
E.A. Jonckheere ◽  
S. Hayati
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.


2021 ◽  
pp. 1-27
Author(s):  
Junde Qi ◽  
Bing Chen ◽  
Dinghua Zhang

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.


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.


1998 ◽  
Vol 64 (626) ◽  
pp. 3874-3880
Author(s):  
Hiroyuki KOYAMA ◽  
Tateki UCHIDA ◽  
Takashi KOMEDA ◽  
Hiroyasu FUNAKUBO ◽  
Kintomo TAKAKURA
Keyword(s):  

1998 ◽  
Vol 64 (626) ◽  
pp. 3881-3887
Author(s):  
Hiroyuki KOYAMA ◽  
Takashi KOMEDA ◽  
Tateki UCHIDA ◽  
Hiroyasu FUNAKUBO ◽  
Kintomo TAKAKURA

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 134224-134232
Author(s):  
Pengfei Xiao ◽  
Hehua Ju ◽  
Qidong Li ◽  
Jijun Meng ◽  
Feifei Chen

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