SCREW KINEMATIC MODEL FOR ROBOT CALIBRATION WITH PC-ROBOT COMMUNICATION OVERVIEW

2017 ◽  
Author(s):  
Lucas Kato ◽  
Tiago Pinto ◽  
Henrique Simas ◽  
Daniel Martins
Keyword(s):  
Kinematic Model ◽  
Robot Calibration ◽  
Robot Communication

A Sensitivity Analysis Based Method for Robot Calibration

1992 ◽  
Author(s):  
S. Kaizerman ◽  
B. Benhabib ◽  
R. G. Fenton ◽  
G. Zak
Keyword(s):  
Sensitivity Analysis ◽  
Kinematic Model ◽  
Calibration Procedure ◽  
Inverse Kinematic ◽  
Model Parameters ◽  
Robot Calibration ◽  
Adjoint Sensitivity ◽  
Analysis Methods ◽  
The Matrix ◽  
Direct Sensitivity

Abstract A new robot kinematic calibration procedure is presented. The parameters of the kinematic model are estimated through a relationship established between the deviations in the joint variables and the deviations in the model parameters. Thus, the new method can be classified as an inverse calibration procedure. Using suitable sensitivity analysis methods, the matrix of the partial derivatives of joint variables with respect to robot parameters is calculated without having explicit expressions of joint variables as a function of task space coordinates (closed inverse kinematic solution). This matrix provides the relationship between the changes in the joint variables and the changes in the parameter values required for the calibration. Two deterministic sensitivity analysis methods are applied, namely the Direct Sensitivity Approach and the Adjoint Sensitivity Method. The new calibration procedure was successfully tested by the simulated calibrations of a two degree of freedom revolute-joint planar manipulator.

Optimization of the Robot Calibration Process

1992 ◽  
Author(s):  
G. Zak ◽  
R. G. Fenton ◽  
B. Benhabib
Keyword(s):  
Optimization Problem ◽  
Kinematic Model ◽  
Optimization Procedure ◽  
Calibration Procedure ◽  
Residual Error ◽  
Industrial Robots ◽  
Multiple Objective Optimization ◽  
Robot Calibration ◽  
Calibration Process ◽  
The Cost

Abstract Most industrial robots cannot be off-line programmed to carry out a task accurately, unless their kinematic model is suitably corrected through a calibration procedure. However, proper calibration is an expensive and time-consuming procedure due to the highly accurate measurement equipment required and due to the significant amount of data that must be collected. To improve the efficiency of robot calibration, an optimization procedure is proposed in this paper. The objective of minimizing the cost of the calibration is combined with the objective of minimizing the residual error after calibration in one multiple-objective optimization. Prediction of the residual error for a given calibration process presents the main difficulty for implementing the optimization. It is proposed that the residual error is expressed as a polynomial function. This function is obtained as a result of fitting a response surface to either experimental or simulated sample estimates of the residual error. The optimization problem is then solved by identifying a reduced set of possible solutions, thus greatly simplifying the decision maker’s choice of an effective calibration procedure. An application example of this method is also included.

Determination of the Optimum Cost-Residual Error Trade-off in Robot Calibration

1994 ◽  
Vol 116 (1) ◽  
pp. 28-35 ◽  
Author(s):  
G. Zak ◽  
R. G. Fenton ◽  
B. Benhabib
Keyword(s):  
Kinematic Model ◽  
Optimization Procedure ◽  
Calibration Procedure ◽  
Residual Error ◽  
Industrial Robots ◽  
Multiple Objective Optimization ◽  
Robot Calibration ◽  
Optimum Cost ◽  
The Cost

Most industrial robots cannot be off-line programmed to carry out a task accurately, unless their kinematic model is suitably corrected through a calibration procedure. However, proper calibration is an expensive and time-consuming procedure due to the highly accurate measurement equipment required and due to the significant amount of data that must be collected. To improve the efficiency of robot calibration, an optimization procedure is proposed in this paper. The objective of minimizing the cost of the calibration is combined with the objective of minimizing the residual error after calibration in one multiple-objective optimization. Prediction of the residual error for a given calibration process presents the main difficulty for implementing the optimization. It is proposed that the residual error is expressed as a polynomial function. This function is obtained as a result of fitting a response surface to either experimental or simulated sample estimates of the residual error. The optimization problem is then solved by identifying a reduced set of possible solutions, thus greatly simplifying the decision maker’s choice of an effective calibration procedure. An application example of this method is also included.

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.

Application of the Weighted Least Squares Parameter Estimation Method to the Robot Calibration

1994 ◽  
Vol 116 (3) ◽  
pp. 890-893 ◽  
Author(s):  
G. Zak ◽  
B. Benhabib ◽  
R. G. Fenton ◽  
I. Saban
Keyword(s):  
Parameter Estimation ◽  
Least Squares ◽  
Weighted Least Squares ◽  
Kinematic Model ◽  
Measurement Data ◽  
Estimation Method ◽  
Kinematic Parameter ◽  
Measuring System ◽  
Parameter Estimates ◽  
Robot Calibration

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.

scholarly journals Robot Calibration combining Kinematic Model and Neural Network for enhanced Positioning and Orientation Accuracy

2020 ◽  
Vol 53 (2) ◽  
pp. 8432-8437
Author(s):  
Stefan Gadringer ◽  
Hubert Gattringer ◽  
Andreas Müller ◽  
Ronald Naderer
Keyword(s):  
Neural Network ◽  
Kinematic Model ◽  
Robot Calibration

scholarly journals Robotic tooling calibration based on linear and nonlinear formulations.

2021 ◽  
Author(s):  
Mohamed Helal
Keyword(s):  
Industrial Robot ◽  
Kinematic Model ◽  
Position Estimation ◽  
Error Model ◽  
Linear Formulation ◽  
Experimental Result ◽  
Robot Calibration ◽  
Nonlinear Formulation ◽  
Self Calibration ◽  
Calibration Methods

Industrial robot calibration packages, such as ABB CalibWare, are developed only for robot calibration. As a result, the robotic tooling systems designed and fabricated by the user are often calibrated in an ad-hoc fashion. In this thesis, a systematic way for robotic tooling calibration is presented in order to overcome this problem. The idea is to include the tooling system as an extended body in the robot kinematic model, from which two error models are established. The first error model is associated with the robot, while the second error model is associated with the tooling. Once the robot is fully calibrated, the first error will be reduced to the required accuracy. Thus, the method is focused on the second error model. For the tool error calibration, two formulations were used. The first is a linear formulation based on conventional calibration as well as self-calibration methods while the second is a nonlinear formulation. The conventional linear formulation was extensively investigated and implemented while the self-calibration was proven to be inadequate for the tooling calibration. Moreover, the nonlinear formulation was demonstrated to be very effective and accurate through experimental result. The end-effector position estimation as well as the tool pose estimation were obtained using a 3D vision system as an off-line error measurement technique.

scholarly journals A Methodology for Industrial Robot Calibration Based on Measurement Sub-Regions

2021 ◽  
Author(s):  
Juan Sebastian Toquica ◽  
José Maurı́cio Motta
Keyword(s):  
Industrial Robot ◽  
Low Cost ◽  
Kinematic Model ◽  
Measurement Data ◽  
Industrial Applications ◽  
Industrial Robots ◽  
Robot Calibration ◽  
High Precision Measurement ◽  
Measurement Systems ◽  
Robot Accuracy

Abstract This paper proposes a methodology for calibration of industrial robots that uses a concept of measurement sub-regions, allowing low-cost solutions and easy implementation to meet the robot accuracy requirements in industrial applications. The solutions to increasing the accuracy of robots today have high-cost implementation, making calibration throughout the workplace in industry a difficult and unlikely task. Thus, reducing the time spent and the measured workspace volume of the robot end-effector are the main benefits of the implementation of the sub-region concept, ensuring sufficient flexibility in the measurement step of robot calibration procedures. The main contribution of this article is the proposal and discussion of a methodology to calibrate robots using several small measurement sub-regions and gathering the measurement data in a way equivalent to the measurements made in large volume regions, making feasible the use of high-precision measurement systems but limited to small volumes, such as vision-based measurement systems. The robot calibration procedures were simulated according to the literature, such that results from simulation are free from errors due to experimental setups as to isolate the benefits of the measurement proposal methodology. In addition, a method to validate the analytical off-line kinematic model of industrial robots is proposed using the nominal model of the robot supplier incorporated into its controller.

A Sensitivity Analysis Based Method for Robot Calibration

1994 ◽  
Vol 116 (2) ◽  
pp. 607-613 ◽  
Author(s):  
S. Kaizerman ◽  
G. Zak ◽  
B. Benhabib ◽  
R. G. Fenton
Keyword(s):  
Sensitivity Analysis ◽  
Kinematic Model ◽  
Calibration Procedure ◽  
Inverse Kinematic ◽  
Model Parameters ◽  
Robot Calibration ◽  
Adjoint Sensitivity ◽  
Analysis Methods ◽  
The Matrix ◽  
Direct Sensitivity

A new robot kinematic calibration procedure is presented. The parameters of the kinematic model are estimated through a relationship established between the deviations in the joint variables and the deviations in the model parameters. Thus, the new method can be classified as an inverse calibration procedure. Using suitable sensitivity analysis methods, the matrix of the partial derivatives of joint variables with respect to robot parameters is calculated without having explicit expressions of joint variables as a function of task space coordinates (closed inverse kinematic solution). This matrix provides the relationship between the changes in the joint variables and the changes in the parameter values required for the calibration. Two deterministic sensitivity analysis methods are applied, namely the Direct Sensitivity Approach and the Adjoint Sensitivity Method. The new calibration procedure was successfully tested by the simulated calibrations of a two-degree-of-freedom revolute-joint planar manipulator.

Sign in / Sign up

Export Citation Format

Share Document