An improved kinematic model for calibration of serial robots having closed-chain mechanisms

Robotica ◽  
2011 ◽  
Vol 30 (6) ◽  
pp. 963-971 ◽  
Author(s):  
Minh To ◽  
Phil Webb
Keyword(s):  
Closed Loop ◽  
Industrial Robot ◽  
Kinematic Model ◽  
Experimental Studies ◽  
Industrial Robots ◽  
Linear Functions ◽  
Serial Link ◽  
Serial Robots ◽  
Proposed Model ◽  
Calibration Techniques

SUMMARYMany industrial robots employ closed-loop actuating elements such as the parallelogram mechanism for increased stiffness. Modeling these manipulators for the purpose of calibration presents a challenge due to complex nonlinear couplings between parameters of the chains. The modeling method presented in this paper involves the integration of the open- and closed-loop elements whose errors can be resolved as linear functions of their parameters. As a result, the model is similar to that of a serial-link robot, which makes it possible to use existing well-defined calibration techniques in the area. Simulation and experimental studies on an industrial robot for verifying the correctness and effectiveness of the proposed model are also described.

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.

scholarly journals Joint Stiffness Identification and Deformation Compensation of Serial Robots Based on Dual Quaternion Algebra

2018 ◽  
Vol 9 (1) ◽  
pp. 65 ◽  
Author(s):  
Guozhi Li ◽  
Fuhai Zhang ◽  
Yili Fu ◽  
Shuguo Wang
Keyword(s):  
Quaternion Algebra ◽  
Industrial Robot ◽  
Joint Stiffness ◽  
Industrial Robots ◽  
Identification Algorithm ◽  
Dual Quaternion ◽  
Compensation Algorithm ◽  
Serial Robots ◽  
Stiffness Identification ◽  
Deformation Compensation

As the application of industrial robots is limited by low stiffness that causes low precision, a joint stiffness identification algorithm for serial robots is presented. In addition, a deformation compensation algorithm is proposed for the accuracy improvement. Both of these algorithms are formulated by dual quaternion algebra, which offers a compact, efficient, and singularity-free way in robot analysis. The joint stiffness identification algorithm is derived from stiffness modeling, which is the combination of the principle of virtual work and dual quaternion algebra. To validate the effectiveness of the proposed identification algorithm and deformation compensation algorithm, an experiment was conducted on a dual arm industrial robot SDA5F. The robot performed a drilling operation during the experiment, and the forces and torques that acted on the end-effector (EE) of both arms were measured in order to apply the deformation compensation algorithm. The results of the experiment show that the proposed identification algorithm is able to identify the joint stiffness parameters of serial industrial robots, and the deformation compensation algorithm can improve the accuracy of the position and orientation of the EE. Furthermore, the performance of the forces and torques that acted on the EE during the operation were improved as well.

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.

Performance Criteria to Evaluate a Kinematically Redundant Robotic Cell for Machining Tasks

2012 ◽  
Vol 162 ◽  
pp. 413-422 ◽  
Author(s):  
Kévin Subrin ◽  
Laurent Sabourin ◽  
Grigore Gogu ◽  
Youcef Mezouar
Keyword(s):  
High Speed ◽  
Dynamic Capabilities ◽  
Industrial Robot ◽  
Kinematic Model ◽  
Geometrical Model ◽  
Industrial Robots ◽  
Machining Process ◽  
Performance Criteria ◽  
Robotic Cell ◽  
Speed Accuracy

Machine tools and robots have both evolved fundamentally and we can now question the abilities of new industrial robots concerning accurate task realization under high constraints. Requirements in terms of kinematic and dynamic capabilities in High Speed Machining (HSM) are increasingly demanding. To face the challenge of performance improvement, parallel and hybrid robotic architectures have emerged and a new generation of industrial serial robots with the ability to perform machining tasks has been designed. In this paper, we propose to evaluate the performance criteria of an industrial robot included in a kinematically redundant robotic cell dedicated to a machining task. Firstly, we present the constraints of the machining process (speed, accuracy etc.). We then detail the direct geometrical model and the kinematic model of a robot with closed chain in the arm and we propose a procedure for managing kinematic redundancy whilst integrating various criteria. Finally, we present the evolution of the criteria for a given trajectory in order to define the best location for a rotary table and to analyze the manipulators stiffness.

Calibration and Compensation of Rotary Axis Angular Positioning Deviations on a SCARA-Type Industrial Robot Using a Laser Tracker

2020 ◽  
Author(s):  
Nan Zhao ◽  
Soichi Ibaraki
Keyword(s):  
Rotation Axis ◽  
Industrial Robot ◽  
Kinematic Model ◽  
Industrial Robots ◽  
Laser Tracker ◽  
Link Length ◽  
Positional Accuracy ◽  
Positioning Accuracy ◽  
Rotary Axis ◽  
The Absolute

Abstract In general, the “absolute” positioning accuracy of industrial robots is significantly lower than its repeatability. In the past research, in order to improve a robot’s positioning accuracy over the entire workspace, the compensation for the link length errors and the rotation axis angle offsets are often employed. However, the positioning error of the compensated industrial robot is still much higher than that of a typical machine tool. The purpose of this study is to propose a new kinematic model and its calibration scheme to further improve the absolute positional accuracy of an industrial robot over the entire workspace. In order to simplify the problem, this study only targets the 2D positioning accuracy of a SCARA-type robot. The proposed model includes not only link length errors and rotary axis angular offsets but also the “error map” of the angular positioning deviation of each rotary axis. The angular error deviation of each rotary axis is identified by measuring the robot’s end-effector position by a laser tracker at many positions. To verify the validity of the identified model, the effectiveness of the compensation based on it is also investigated.

An improved minimal error model for the robotic kinematic calibration based on the POE formula

Robotica ◽  
2021 ◽  
pp. 1-20
Author(s):  
Ruiqing Luo ◽  
Wenbin Gao ◽  
Qi Huang ◽  
Yi Zhang
Keyword(s):  
Least Squares Method ◽  
Industrial Robot ◽  
Kinematic Model ◽  
Error Model ◽  
Coordinate Frame ◽  
Exponential Map ◽  
Kinematic Calibration ◽  
Minimal Error ◽  
Serial Robots ◽  
Calibration Algorithm

Summary The conventional product of exponentials $\left(\rm POE\right)$ -based methods dissatisfy the parametric minimality for the kinematic calibration of serial robots due to overlooking the magnitude and pitch constraints. Thus, the minimal kinematic model is presented to solve this problem, which can be developed further. This paper puts forward an improved algorithm for the minimal parameter calibration. An actual kinematic model with the minimal parameters $\left(\rm MP\right)$ is constructed according to the geometric properties of actual joint twists in the auxiliary frames established on the basis of the nominal joint axes. Then, the initial pose error is defined in the tool coordinate frame, which is expressed as the exponential map of the twist, and all twist descriptions are unified, so as to give a unified kinematic model in mathematics. By differentiating the kinematic model, a minimal error model is derived in explicit form. Subsequently, we propose a novel parameter identification method, which identifies the orientation error and position error parameters separately by the iterative least-squares method and updates the MP uniformly. Finally, the simulations and experiments on the different serial robots are conducted to verify the correctness and effectiveness of the proposed algorithm. The simulation results show our calibration algorithm outperforms the existing ones in the accuracy aspect, and the experiment result shows that the absolute pose accuracy of the UR5 industrial robot is upgraded about 9 times under a statistics sense after the calibration.

scholarly journals Kinematic Calibration of Industrial Robots Based on Distance Information Using a Hybrid Identification Method

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Guanbin Gao ◽  
Yuan Li ◽  
Fei Liu ◽  
Shichang Han
Keyword(s):  
Industrial Robot ◽  
Kinematic Model ◽  
Error Model ◽  
Industrial Robots ◽  
Kinematic Calibration ◽  
Kinematic Parameters ◽  
Distance Information ◽  
End Effector ◽  
Hybrid Identification ◽  
Identification Method

To improve the positioning accuracy of industrial robots and avoid using the coordinates of the end effector, a novel kinematic calibration method based on the distance information is proposed. The kinematic model of an industrial robot is established. The relationship between the moving distance of the end effector and the kinematic parameters is analyzed. Based on the results of the analysis and the kinematic model of the robot, the error model with displacements as the reference is built, which is linearized for the convenience of the following identification. The singular value decomposition (SVD) is used to eliminate the redundant parameters of the error model. To solve the problem that traditional optimization algorithms are easily affected by data noise in high dimension identification, a novel extended Kalman filter (EKF) and regularized particle filter (RPF) hybrid identification method is presented. EKF is used in the preidentification of the linearized error model. With the preidentification results as the initial parameters, RPF is used to identify the kinematic parameters of the linearized error model. Simulations are carried out to validate the effectiveness of the proposed method, which shows that the method can identify the error of the parameters and after compensation the accuracy of the robot is improved.

scholarly journals Experimental studies of robotic assembly of precision parts

2021 ◽  
Vol 49 (1) ◽  
pp. 44-55
Author(s):  
Mikhail Polishchuk ◽  
M. Tkach
Keyword(s):  
High Speed ◽  
Industrial Robot ◽  
Economic Effect ◽  
Experimental Studies ◽  
Industrial Robots ◽  
Robotic Assembly ◽  
Robot Arm ◽  
Positioning Accuracy ◽  
Position Correction ◽  
The Cost

At present, robotization of assembly processes is achieved through the use of industrial robots with high positioning accuracy in conjunction with tactile means of adaptation to the conditions of assembly of precision parts. The cost of such robots is many times higher than the cost of simple robots with low positioning accuracy of the robot arm. The research in this article is aimed at reducing the cost of assembly processes for precision parts by applying the position correction of the connected parts not by the robot hand, but by an additional technological module that is installed on the manipulator of a simple robot and performs high-speed stochastic mismatch scan of assembly objects. The article presents the results of a full factorial experiment of the process of joining precision cylindrical parts with a gap of no more than 3...5 microns. A regression model of this process is proposed, a formula for calculating the quasi-optimal modes of precision assembly and graphanalytical dependences of the assembly time on the scanning modes of the misalignment of assembly objects are given. The proposed high-speed method for compensating for the positioning error of an industrial robot makes it possible to assemble precision parts in a very short time within 1...3(s). The main economic effect of the research results is that the device for scanning the misalignment of assembly objects, which is installed on the arm of an inexpensive robot with a low positioning accuracy, can significantly increase the assembly speed and reduce capital investments in robotic assembly of high-precision parts.

A four-point measurement model for evaluating the pose of industrial robot and its influence factor analysis

2017 ◽  
Vol 44 (3) ◽  
pp. 343-352 ◽  
Author(s):  
Chuangui Yang ◽  
Junwen Wang ◽  
Liang Mi ◽  
Xingbao Liu ◽  
Yangqiu Xia ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Measurement Uncertainty ◽  
Measurement Accuracy ◽  
Influence Factor ◽  
Industrial Robot ◽  
Measurement Model ◽  
Industrial Robots ◽  
Content Type ◽  
Point Measurement ◽  
Proposed Model

Purpose This paper aims to propose a four-point measurement model for directly measuring the pose (i.e. position and orientation) of industrial robot and reducing its calculating error and measurement uncertainty. Design/methodology/approach A four-point measurement model is proposed for directly measuring poses of industrial robots. First, this model consists of a position measurement model and an orientation model gotten by the position of spherically mounted reflector (SMR). Second, an influence factor analysis, simulated by Monte Carlo simulation, is performed to investigate the influence of certain factors on the accuracy and uncertainty. Third, comparisons with the common method are carried out to verify the advantage of this model. Finally, a test is carried out for evaluating the repeatability of five poses of an industrial robot. Findings In this paper, results show that the proposed model is better than the three-SMRs model in measurement accuracy, measurement uncertainty and computational efficiency. Moreover, both measurement accuracy and measurement uncertainty can be improved by using the proposed influence laws of its key parameters on the proposed model. Originality/value The proposed model can measure poses of industrial robots directly, accurately and effectively. Additionally, influence laws of key factors on the accuracy and uncertainty of the proposed model are given to provide some guidelines for improving the performance of the proposed model.

A Relativistic Newtonian Mechanics Predicts with Precision the Results of Recent Neutrino-Velocity Experiments

2014 ◽  
Vol 6 (1) ◽  
pp. 1032-1035 ◽  
Author(s):  
Ramzi Suleiman
Keyword(s):  
Null Hypothesis ◽  
Experimental Studies ◽  
Theoretical Models ◽  
Newtonian Mechanics ◽  
Speed Of Light ◽  
Symmetry Principle ◽  
Proposed Model ◽  
Significant Difference ◽  
The One ◽  
Complete Collapse

The research on quasi-luminal neutrinos has sparked several experimental studies for testing the "speed of light limit" hypothesis. Until today, the overall evidence favors the "null" hypothesis, stating that there is no significant difference between the observed velocities of light and neutrinos. Despite numerous theoretical models proposed to explain the neutrinos behavior, no attempt has been undertaken to predict the experimentally produced results. This paper presents a simple novel extension of Newton's mechanics to the domain of relativistic velocities. For a typical neutrino-velocity experiment, the proposed model is utilized to derive a general expression for . Comparison of the model's prediction with results of six neutrino-velocity experiments, conducted by five collaborations, reveals that the model predicts all the reported results with striking accuracy. Because in the proposed model, the direction of the neutrino flight matters, the model's impressive success in accounting for all the tested data, indicates a complete collapse of the Lorentz symmetry principle in situation involving quasi-luminal particles, moving in two opposite directions. This conclusion is support by previous findings, showing that an identical Sagnac effect to the one documented for radial motion, occurs also in linear motion.

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