Study on Two-Step Method for Robot Dynamics Parameters Calibration

2012 ◽  
Vol 605-607 ◽  
pp. 1557-1562 ◽  
Author(s):  
Qing Xuan Jia ◽  
Tong Li ◽  
Gang Chen
Keyword(s):  
Inverse Method ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Second Step ◽  
Robot Dynamics ◽  
Joint Movement ◽  
Step Method ◽  
Multidimensional Matrix ◽  
Pseudo Inverse

In order to obtain accurate dynamics parameters, a two-step method for robot dynamics parameters calibration is presented. In the first step a multidimensional matrix is constituted through transforming the configurations of robot manipulators and the product of quality and centroid coordinate about links is solved by using the least square method. In the second step decoupling dynamic equation of robot is deduced based on Newton-Euler algorithm, and through planning specific joint movement, the inertia tensor and centroid coordinate of robot links are calibrated making use of the pseudo inverse method. By the above two steps, the entire calibration of robot dynamic parameters is achieved. The correctness and feasibility of the presented calibration method is manifested by simulations and experiments.

scholarly journals The tides in the south-western Kara sea. Tides calibration method effects

2017 ◽  
pp. 98-115
Author(s):  
G. N. Voinov ◽  
A. K. Naumov
Keyword(s):  
Sea Level ◽  
Least Square Method ◽  
Calibration Method ◽  
Kara Sea ◽  
Least Square ◽  
The South ◽  
Quality Estimation ◽  
Annual Series ◽  
Method Effects ◽  
Statistical Estimations

The estimates of the tides harmonic constants are given over the period from 1962 to 1993. They were received using a least square method according to AARI. Quality estimation of the sea level observations was performed. The annual series with bad observations were transformed by means of tides calibration. The Estimation of the tides fi ne structure – harmonics of the second and third degree of the potential according to analysis over the period from 1962–1985 was received. The statistical estimations of the sea level in the separate typical years were calculated using initial and corrected series.

scholarly journals Self-Calibration of an Industrial Robot Using a Novel Affordable 3D Measuring Device

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3380 ◽  
Author(s):  
Martin Gaudreault ◽  
Ahmed Joubair ◽  
Ilian Bonev
Keyword(s):  
Industrial Robot ◽  
Low Cost ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Geometrical Parameters ◽  
Robot Arm ◽  
Measuring Device ◽  
Self Calibration ◽  
Position Errors

This work shows the feasibility of calibrating an industrial robot arm through an automated procedure using a new, low-cost, wireless measuring device mounted on the robot’s flange. The device consists of three digital indicators that are fixed orthogonally to each other on an aluminum support. Each indicator has a measuring accuracy of 3 µm. The measuring instrument uses a kinematic coupling platform which allows for the definition of an accurate and repeatable tool center point (TCP). The idea behind the calibration method is for the robot to bring automatically this TCP to three precisely-known positions (the centers of three precision balls fixed with respect to the robot’s base) and with different orientations of the robot’s end-effector. The self-calibration method was tested on a small six-axis industrial robot, the ABB IRB 120 (Vasteras, Sweden). The robot was modeled by including all its geometrical parameters and the compliance of its joints. The parameters of the model were identified using linear regression with the least-square method. Finally, the performance of the calibration was validated with a laser tracker. This validation showed that the mean and the maximum absolute position errors were reduced from 2.628 mm and 6.282 mm to 0.208 mm and 0.482 mm, respectively.

Camera Calibration Based on Snell’s Law

2005 ◽  
Vol 128 (3) ◽  
pp. 548-557 ◽  
Author(s):  
Psang Dain Lin ◽  
Chi-Kuen Sung
Keyword(s):  
Camera Calibration ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Camera System ◽  
Optical Elements ◽  
Snell’S Law ◽  
Snell's Law ◽  
Geometric Relationship ◽  
Pinhole Model

In this paper we present a camera calibration method using Snell’s Law. Traditional camera calibration is based on the pinhole model, which is an approximation algorithm using untrue geometrical assumptions and giving a single lumped result for the various optical elements in the camera system. Using full modeling of lens geometry, the proposed method establishes the geometric relationship between images and objects via Snell’s Law. A matrix equation that relates the intrinsic/extrinsic parameters of image the plane and six pose parameters of each element is determined from sensitivity analysis. These parameters can be identified using the least square method by observing points with known coordinates. An illustrative example using a two-camera stereo coordinate measurement system demonstrates that system performance via the proposed method is better than the pinhole model.

A Camera Calibration Method Based on Free Points

2011 ◽  
Vol 130-134 ◽  
pp. 1885-1888
Author(s):  
Jing Lei Zhang ◽  
Kai Bo Fan ◽  
Yan Jiao Wang
Keyword(s):  
Standard Deviation ◽  
Ccd Camera ◽  
Least Square Method ◽  
Calibration Method ◽  
Initial Guess ◽  
Least Square ◽  
Camera Model ◽  
Extrinsic Parameters ◽  
The Mean ◽  
Constraint Method

A new accurate calibrating technique for intrinsic parameters and extrinsic parameters of CCD camera is described. The camera model is derived by the pinhole projection theory. Then other parameters of the model are resolved under the radial alignment constraints and orthogonal constraints. In order to get a fine initial guess for the nonlinear searching solution, the least square method is introduced, and finally uses radial alignment constraint method to get the results. The experimental results show that the mean absolute differences in x direction and y direction are 0.0070 and 0.1430 separately while the standard deviation are 0.5006 and 1.2046 separately.

The Novel Calibration Method for 3-DOF Measurement System

2011 ◽  
Vol 120 ◽  
pp. 440-443
Author(s):  
Kwang Il Lee ◽  
Jin Seok Jang ◽  
Hyun Woo Lee ◽  
Suk Jin Kim ◽  
Sang Ryong Lee ◽  
...  
Keyword(s):  
Measurement System ◽  
Measurement Accuracy ◽  
Least Square Method ◽  
Calibration Method ◽  
Measured Data ◽  
Least Square ◽  
The Novel ◽  
Squareness Error ◽  
Misalignment Error ◽  
Calibration Parameters

In this paper, a novel calibration method is developed to improve the measurement accuracy of 3-DOF measurement system. The squareness error between three sensors and misalignment error with respect to reference coordinate of machine tool are calibration parameters. To estimate these parameters, reference ball is used and moved in the measuring ranges of 3-DOF measurement system. The relation between calibration parameters, position of reference ball, measured data of sensors are defined using geometric constraint and estimated using least square method. Finally, simulation is done to check the feasibility of developed calibration method. The result of simulation revealed the validation of developed method.

An improved kinematic calibration method for serial manipulators based on POE formula

Robotica ◽  
2018 ◽  
Vol 36 (8) ◽  
pp. 1244-1262 ◽  
Author(s):  
Chenguang Chang ◽  
Jinguo Liu ◽  
Zhiyu Ni ◽  
Ruolong Qi
Keyword(s):  
High Precision ◽  
Least Square Method ◽  
Calibration Method ◽  
Error Model ◽  
Least Square ◽  
Identification Accuracy ◽  
Kinematic Calibration ◽  
Serial Manipulators ◽  
Serial Robots ◽  
Generic Modeling

SUMMARYExisting measurement equipments easily determine position with high precision. However, they evaluate orientation with low precision. It is necessary to minimize the effect of measurement error on identification accuracy. In this study, a method for kinematic calibration based on the product of exponentials (POE) is presented to improve the absolute positioning accuracy of a sliding manipulator. An error model with uniform and generic modeling rules is established in which the tool frame is selected as the reference frame. Furthermore, the redundant parameters of the error model are removed. Subsequently, the actual kinematic parameters are identified by using the least square method. Finally, the process of the improved method is discussed. Kinematic calibration simulations of a sliding manipulator are implemented. The results indicate that the proposed method significantly improves the precision of the sliding manipulator. The improved POE kinematic calibration method offers convenience, efficiency, and high precision. The proposed method can be applied to all types of serial robots with n-DOF

scholarly journals DOA Estimation and Self-Calibration under Unknown Mutual Coupling

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 978
Author(s):  
Dong Qi ◽  
Min Tang ◽  
Shiwen Chen ◽  
Zhixin Liu ◽  
Yongjun Zhao
Keyword(s):  
Mutual Coupling ◽  
Linear Equations ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Frequency Distributions ◽  
Steering Vector ◽  
Practical Applications ◽  
Time Frequency ◽  
Self Calibration

In practical applications, the assumption of omnidirectional elements is not effective in general, which leads to the direction-dependent mutual coupling (MC). Under this condition, the performance of traditional calibration algorithms suffers. This paper proposes a new self-calibration method based on the time-frequency distributions (TFDs) in the presence of direction-dependent MC. Firstly, the time-frequency (TF) transformation is used to calculate the space-time-frequency distributions (STFDs) matrix of received signals. After that, the estimated steering vector and corresponding noise subspace are estimated by the steps of noise removing, single-source TF points extracting and clustering. Then according to the transformation relationship between the MC coefficients, steering vector and MC matrix, we deduce a set of linear equations. Finally, with two-step alternating iteration, the equations are solved by least square method in order to estimate DOA and MC coefficients. Simulations results show that the proposed algorithm can achieve direction-dependent MC self-calibration and outperforms the existing algorithms.

scholarly journals Application of PCA Analysis and QR Decomposition to Address RFM's Ill-Posedness

2020 ◽  
Vol 86 (1) ◽  
pp. 17-21 ◽  
Author(s):  
Amin Alizadeh Naeini ◽  
Sayyed Hamed Alizadeh Moghaddam ◽  
Mohammad Moein Sheikholeslami ◽  
AliReza Amiri-Simkooei
Keyword(s):  
Control Point ◽  
Principal Component ◽  
Least Square Method ◽  
Qr Decomposition ◽  
Least Square ◽  
Design Matrix ◽  
Step Method ◽  
Small Perturbations ◽  
Sensor Model ◽  
Highly Correlated

Rational function model (<small>RFM</small>) is the most widely used sensor model in the remote sensing community. However, it suffers from ill-posedness, challenging its feasibility. This problem, i.e., ill-posedness, is mainly caused due to highly correlated coefficients of the <small>RFM</small>, which magnifies any small perturbations of observations, such as noise and instrumental error. This paper outlines a novel two-step method, called principal component analysis (<small>PCA</small>)-<small>RFM</small>, based on the integration of <small>PCA</small> and QR decomposition. In the first step, the <small>PCA</small>-<small>RFM</small> reduces the observational perturbations from the design matrix using the <small>PCA</small>. In the next step, the <small>RFM</small>'s coefficients are estimated using a <small>QR</small> decomposition with column pivoting and least square method. According to the results, the <small>PCA</small>-<small>RFM</small> is less sensitive than its rivals to the changes of the ground control point (<small>GCPs</small>) distribution. Geometrically speaking, in addition, <small>PCA</small>-<small>RFM</small> is more accurate than recently established methods even in the presence of the small number of <small>GCPs</small>.

scholarly journals Improve three-dimensional point localization accuracy in stereo vision systems using a novel camera calibration method

2020 ◽  
Vol 17 (1) ◽  
pp. 172988141989671 ◽  
Author(s):  
Luis R Ramírez-Hernández ◽  
Julio C Rodríguez-Quiñonez ◽  
Moises J Castro-Toscano ◽  
Daniel Hernández-Balbuena ◽  
Wendy Flores-Fuentes ◽  
...  
Keyword(s):  
Camera Calibration ◽  
Stereo Vision ◽  
Autonomous Navigation ◽  
Three Dimensional ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Vision Systems ◽  
Localization Accuracy ◽  
Calibration Methods

Computer vision systems have demonstrated to be useful in applications of autonomous navigation, especially with the use of stereo vision systems for the three-dimensional mapping of the environment. This article presents a novel camera calibration method to improve the accuracy of stereo vision systems for three-dimensional point localization. The proposed camera calibration method uses the least square method to model the error caused by the image digitalization and the lens distortion. To obtain particular three-dimensional point coordinates, the stereo vision systems use the information of two images taken by two different cameras. Then, the system locates the two-dimensional pixel coordinates of the three-dimensional point in both images and coverts them into angles. With the obtained angles, the system finds the three-dimensional point coordinates through a triangulation process. The proposed camera calibration method is applied in the stereo vision systems, and a comparative analysis between the real and calibrated three-dimensional data points is performed to validate the improvements. Moreover, the developed method is compared with three classical calibration methods to analyze their advantages in terms of accuracy with respect to tested methods.

scholarly journals Research on Calibration Method for Tractor Automatic Navigation Control System

2016 ◽  
Vol 10 (1) ◽  
pp. 129-140 ◽  
Author(s):  
Qun Sun ◽  
Shaomin Teng ◽  
Yongqi Du ◽  
Ze Kang ◽  
Chengqiang Yin ◽  
...  
Keyword(s):  
Control System ◽  
Computer Control ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Output Unit ◽  
Computer Control System ◽  
Automatic Navigation ◽  
Conversion Unit ◽  
Hydraulic Valves

A lower computer control system of tractor automatic navigation based on double-antennas Beidou satellite is developed, including the controller unit, bipolar output unit, RS232 bus communication unit, a switch reset unit and the power conversion unit. To obtain a continuous voltage output, the calibration method of lower control system using least square method to fit calibration curve has been studied. The lower computer control system receives navigation angel and navigation angel offset instruction provided by the host computer through RS232 bus communication unit. Continuous voltage from -10V to +10V is output through the bipolar output unit to adjust hydraulic valves to control the tractor steering after these are processed by the lower computer.

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