On a Relationship Between the Physical Features of Robotic Manipulators and the Kinematic Parameters Produced by Numerical Calibration

1993 ◽  
Vol 115 (4) ◽  
pp. 892-900 ◽  
Author(s):  
A. Goswami ◽  
J. R. Bosnik

Although kinematic parameter estimation is well-established as a technique for improving the positioning accuracy of a robotic manipulator, little attention has been given to the relationship between the parameters of a kinematic model and the corresponding physical features of a manipulator. If each kinematic parameter of a robot corresponds to one and only one of its independent physical features, then a change in the value of an optimal parameter would reflect a change in the corresponding physical feature. This knowledge is of potential value in isolating the sources of wear and damage in a manipulator, and, more generally, in predictive maintenance. In this work, the choice of kinematic model is shown to have a strong effect on the physical feature/kinematic parameter relationship. The most suitable kinematic model for preserving this relationship includes redundant parameters, which may interact numerically among themselves during the parameter estimation process and may complicate the interpretation of results. On the other hand, a kinematic model with no redundant parameters contains too few parameters to establish a comprehensive physical features/kinematic parameters relationship. Multiple-site pose measurement has been explored as a method of preserving the desired relationship even in the presence of redundant parameters.

1994 ◽  
Vol 116 (3) ◽  
pp. 890-893 ◽  
Author(s):  
G. Zak ◽  
B. Benhabib ◽  
R. G. Fenton ◽  
I. Saban

Significant attention has been paid recently to the topic of robot calibration. To improve the robot’s accuracy, various approaches to the measurement of the robot’s position and orientation (pose) and correction of its kinematic model have been proposed. Little attention, however, has been given to the method of estimation of the kinematic parameters from the measurement data. Typically, a least-squares solution method is used to estimate the corrections to the parameters of the model. In this paper, a method of kinematic parameter estimation is proposed where a standard least-squares estimation procedure is replaced by weighted least-squares. The weighting factors are calculated based on all the a priori available statistical information about the robot and the pose-measuring system. By giving greater weight to the measurements made where the standard deviation of the noise in the data is expected to be lower, a significant reduction in the error of the kinematic parameter estimates is made possible. The improvement in the calibration results was verified using a calibration simulation algorithm.


2014 ◽  
Vol 6 ◽  
pp. 810684 ◽  
Author(s):  
Tie Zhang ◽  
Liang Du ◽  
Xiaoliang Dai

In order to improve the positioning accuracy of robots in the workspace, the maximum cube of robots is solved according to ISO 9283:1998 standard. In addition, in order to efficiently test and identify the kinematic parameters of robots, a mapping from robot's distance error onto kinematic parameter errors is presented based on Hayati's modified D-H model. Then, by analyzing the condition number of distance error matrix, it is concluded that parameter d i can be deleted when parameter β i is added in the joint of the modified model. Furthermore, by analyzing the relationship among the parameters of the distance error model, it is found that the deletion of some unidentified kinematic parameters may not result in the accuracy decrease of kinematic error model. Finally, some compensation experiments of the proposed model without unidentified kinematic parameters are carried out by using a laser tracker system. The results show that the proposed method effectively reduces the distance error and greatly improves the positioning accuracy of robots.


2004 ◽  
Vol 95 (2) ◽  
pp. 517-550 ◽  
Author(s):  
William M. Grove

This article first explains concepts in taxometrics, including the meaning of “taxon” in relation to taxometric procedures. It then mathematically develops the MAXSLOPE procedure of Grove and Meehl which relies on nonlinear regression of one taxometric indicator variable on another. Sufficient conditions for MAXSLOPE's validity are set forth. The relationship between the point of maximum regression slope (MAXSLOPE point) and the HITMAX cut, i.e., the point on a variable which, if used as a diagnostic cut-off score, yields maximum classification accuracy, is analyzed. A sufficient condition is given for the MAXSLOPE point to equal the HITMAX cut; however, most distributions have different MAXSLOPE and HITMAX points. Equations and an algorithm are spelled out for making a graphical test for the existence of a taxon, estimating taxometric parameters, and conducting consistency tests; the latter serve as stringent checks on the validity of a taxonic conjecture. The plausibility of assumptions made, in deriving MAXSLOPE equations, is discussed, and the qualitative effects of violations of these assumptions are explained.


Sign in / Sign up

Export Citation Format

Share Document