Improved Calibration Method Research Articles

A single-pose series sphere-based calibration method for camera-projector structured light system

Camera-projector structured light sensor plays a crucial part in three-dimensional (3D) reconstruction and robot vision fields. Calibration of the camera-projector structured light system is essential for further measurement. The common-used plane-based calibration method is always not flexible due to the inevitable manual adjustment of multi-pose plane. In this paper, a single-pose series sphere-based calibration method is proposed, which mainly includes two steps. The first step is to calibrate the camera’s intrinsic parameters. An improved calibration method based on the image of absolute conic (IAC) is proposed in this step to achieve higher calibration accuracy, and the minimum number of spheres used in this improved method is analyzed. The second step is to calibrate the projector’s intrinsic and extrinsic parameters. In order to achieve the 3D coordinates of feature points on the spherical surface, an accurate method based on the back projection theory is proposed in this step. Finally, calibration experiment for a camera-projector structured light system is implemented, and the experimental result demonstrates that the proposed method can achieve desired flexibility, robustness and accuracy.

Review of Calibration and Improvement Methods of Light- Scattering Airborne Particle Concentration

Clean environment and its internal airborne particle concentration have been paid more and more attention, the demand for use and measurement of light-scattering airborne particle counter, as the main instrument for measuring airborne particle concentration, has increased synchronously. This paper untangles the worldwide standards and specifications for calibration of light-scattering airborne particle counter, analyses the shortcomings of traditional comparative calibration method, introduces the research progress of non-traditional calibration method based on statistical analysis of membrane and scanning electron microscope, then based on the theory of discrete phase model and gas-solid fluid dynamics, puts forward two improved calibration methods to obtain more reliable "true value" of the number of the standard particles passing through the calibrated OPC, to provide an innovative idea for improving the measurement accuracy of airborne particle concentration worldwide.

An Improved Complex Signal-Based Calibration Method for Beam-Steering Phased Array

Phased array calibration is essential to ensureaccurate array radiation performance. This letter proposes an improved calibration method based on complex signals in an anechoic chamber for phased arrays that can only operate in its default beam-steering mode with limited beam-steering angular ranges. The basic principle is to convert the array factors associated with the multiprobe locations into the beam-steering factors of the array, which can virtually widen the beam-steering angular range. The broadened angular range can lower the condition number of the phase setting matrix and therefore improve the calibration accuracy. Both theoretical derivations and measurement validation are provided to demonstrate the effectiveness and enhancement of the proposed method.

3D reconstruction of structured light based on infrared MEMS

The traditional 3D reconstruction process of structured light is based on a DLP visible light grating projection method; the DLP method has many flaws, including great bulk, and harmful to human eyes caused by visible light and so on. In this article, we propose a method based on infrared micro electro mechanical systems (MEMS) instead of DLP to generate programmable coded structured light. First, MEMS emits a laser beam by using a point-beam laser. Then, the laser beam is modulated by the optical system and transformed into a laser line, which is reflected by MEMS and projected onto the object to be measured. The grating pattern can be a square wave or a sinusoidal wave for different needs. Due to the speckle characteristics of the infrared laser, the phase error obtained by the traditional four-step phase-shifting method is very large. Therefore, an eight-step phase-shifting method based on the Gaussian filter is proposed to improve the decoding accuracy of the grating. An improved calibration method based on phase space is used to calibrate the monocular system. Finally, the 3D data of the object are obtained according to this method, and the 3D reconstruction accuracy is better than 0.1 mm.

An Improved Calibration Method to Determine the Strain Coefficient for Optical Fibre Sensing Cables

The strain coefficient of an optical fibre sensing cable is a critical parameter for a distributed optical fibre sensing system. The conventional tensile load test method tends to underestimate the strain coefficient of sensing cables due to slippage or strain transfer loss at the fixing points during the calibration procedure. By optimizing the conventional tensile load test setup, the true strain of a sensing cable can be determined by using two sets of displacement measuring equipment. Thus, the strain calculation error induced by slippage or strain transfer loss between a micrometre linear stage and sensing cable can be avoided. The performance of the improved calibration method was verified by using three types of sensing cables with different structures. In comparison to the conventional tensile load test method, the strain coefficients obtained by the improved calibration method for sensing cables A, B, and C increase by 1.52%, 2.06%, and 1.86%, respectively. Additionally, the calibration errors for the improved calibration method are discussed. The test results indicate that the improved calibration method has good practicability and enables inexperienced experimenters or facilities with limited equipment to perform precise strain coefficient calibration for optical fibre sensing cables.

Improved calibration method for refraction errors in multibeam bathymetries with a wider range of water depths

Errors induced by inaccurate or insufficient sound speed profiles (SSPs) in the water column will cause refraction errors in multibeam bathymetries. Most existing methods focus on eliminating errors in shallow water. Thus, to address the problems in a wider range of water depths, a new method is developed. First, beams in each ping are divided into two parts with the nadir beam as a boundary, and beams in each part have one equivalent sound speed profile (ESSP). Then, the overlaps of adjacent swaths are used to estimate the gradients of ESSPs by minimizing the depth difference in the overlaps with the differential evolution (DE) algorithm. To verify the proposed method, two datasets, i.e., one with artificially introduced refraction errors from water depths within 24 m and the other with refraction errors from water depths within 300 m, are calibrated. The results show that the mean and standard deviation (SD) of the depth difference between the results of the proposed method and the in situ measurements in the shallow water data are approximately -0.006 m and 0.006 m, respectively. The mean and SD of the depth difference between the results of the proposed method and the in situ measurements in the deeper water data are approximately less than -0.066 m and 0.266 m, respectively.

An improved calibration method of the K&C model for modeling steel-fiber reinforced concrete

The K&C material model, one of the widely used concrete models implemented in LS-DYNA for blast or impact analysis, is modified to improve its numerical accuracy for steel-fiber reinforced concrete (SFRC). Many input parameters are required in this model to describe the material properties of SFRC. To address this, an improved calibration method that can easily predict the stress–strain relationships of SFRC by modifying the three strength surfaces and the damage function η(λ) based on uniaxial and triaxial compression data from previous studies is proposed in this paper. The calibration method is verified by single element tests for unconfined uniaxial and triaxial compressive data. In addition, with the introduction of the dynamic increase factor (DIF), a finite element model is produced to demonstrate the validity and applicability of the proposed method through comparison with the experimental results of SFRC slabs subjected to projectile impact.

Improved Camera Calibration Method and Accuracy Analysis for Binocular Vision

The quality of the stereo camera calibration method governs the accuracy of the binocular vision and thus determines the precision of the 3D reconstruction. Spurred by that, in this paper, we propose an improved calibration method that increases the calibration accuracy by optimizing the captured corners. Our method is multi-staged, where first, we employ the Harris corner detector to identify the uncertainties of all image corners. Then, for each detected corner, we apply a linear optimization, and finally, we calibrate the intrinsic and extrinsic parameters of the binocular vision setup by employing a nonlinear optimization scheme. We confirm the validity of our technique by analyzing the factors influencing the camera calibration accuracy and confirm the experimental conditions. Ultimately, we evaluate the proposed method and demonstrate that the mean error of our binocular vision architecture is more appealing compared to current literature.

Kinematic calibration of a 5-axis parallel machining robot based on dimensionless error mapping matrix

Accuracy problem is one of the most challenging issues for the application of parallel robots in manufacturing industry, and kinematic calibration is a feasible approach to solve it. Although lots of researches have brought up a diversity of calibration methods, there are still rooms for the improvement of the accuracy, efficiency and robustness of these calibration effects. In this paper, an improved method for kinematic calibration of a 5-axis parallel machining robot is proposed, which includes a new forward kinematic solution (FKS) based on dual quaternion and a modified error modeling process leading to dimensionless error mapping matrixes (EMMs). On this basis, an iterative identification procedure is schemed, and the kinematics and identification simulations are carried out. The kinematics simulation results show that the proposed FKS has wider convergence range and faster computation speed than Levenberg-Marquardt algorithm, while the identification simulation results show that the residual pose errors with the proposed dimensionless EMMs are lower than that with the conventional EMM in various units. Additionally, the procedure of the full pose measurement with a laser tracker and an auxiliary tool is introduced, and thereby the contrast experiments of kinematic calibration on the prototype are conducted. The experiment results indicate that the residual position and orientation errors based on the dimensionless EMM decrease by 97.67% and 86.85% of the original values, respectively, at least, and by 76.77% and 38.65% of that based on the conventional EMM, respectively, at most. Consequently, it is further confirmed that the proposed calibration method is effective in enhancing the identification accuracy of the geometric errors and improving the positioning accuracy of the studied parallel robot.

A Gyro-Aided Strapdown Triaxial Magnetometer Calibration Method Robust to Gyro Bias

Geomagnetic vector field is always measured by a strapdown triaxial magnetometer on a vehicle. The magnetometer measurements are polluted by the magnetometer inherent errors, misalignment error, and vehicle-generated magnetic inferences. With the aid of absolute attitude information from the gyro, the calibration accuracy has been proved to be greatly improved, especially for vector measurements. However, the performance of calibration methods is greatly affected by the gyro bias, which causes error accumulated over time in the absolute attitude information. In this work, we propose an improved calibration method robust to gyro bias based on relative attitude information from the gyro. Simulation results indicated that the proposed method can estimate the calibration parameters more accurately and stably than the traditional method when the gyro bias exists. The influence on the calibration accuracy of the different parts of the gyro bias is also analyzed by simulation. Experiment using a low-cost gyro proved that the proposed method can effectively improve the estimation accuracy of the calibration parameters, as the influence on the traditional method of the gyro bias is 2–3 orders of magnitude higher than that on the proposed method.

An Improved Calibration Method for Photonic Mixer Device Solid-State Array Lidars Based on Electrical Analog Delay.

As a typical application of indirect-time-of-flight (ToF) technology, photonic mixer device (PMD) solid-state array Lidar has gained rapid development in recent years. With the advantages of high resolution, frame rate and accuracy, the equipment is widely used in target recognition, simultaneous localization and mapping (SLAM), industrial inspection, etc. The PMD Lidar is vulnerable to several factors such as ambient light, temperature and the target feature. To eliminate the impact of such factors, a proper calibration is needed. However, the conventional calibration methods need to change several distances in large areas, which result in low efficiency and low accuracy. To address the problems, this paper presents an improved calibration method based on electrical analog delay. The method firstly eliminates the lens distortion using a self-adaptive interpolation algorithm, meanwhile it calibrates the grayscale image using an integral time simulating based method. Then, the grayscale image is used to estimate the parameters of ambient light compensation in depth calibration. Finally, by combining four types of compensation, the method effectively improves the performance of depth calibration. Through several experiments, the proposed method is more adaptive to multiscenes with targets of different reflectivities, which significantly improves the ranging accuracy and adaptability of PMD Lidar.

An Improved Calibration Method for the Misalignment Error of a Triaxial Magnetometer and Inertial Navigation System in a Three-Component Magnetic Survey System

In order to calibrate the misalignment error of a triaxial magnetometer and an inertial navigation system in a three-component magnetic survey system, an improved method with easy realization is proposed in this paper. We establish the misalignment error model based on Euler’s theorem. We transform the calibration of misalignment error into estimating calibration parameters to minimize the value of objective function. Then, the nonlinear least squares method is used to estimate the calibration parameters. In the simulation experiment, the deviation between the value and the preset value is within 1 nT. In the field experiment, the fluctuation value of the x, y, and z components reduce to 1.09%, 0.92%, and 1.28%, respectively. The absolute deviation values are reduced to 0.72%, 0.70%, and 0.81% and the standard deviation value are reduced to 0.74%, 0.71%, 0.86%, respectively. The proposed method has advantages of high operability and precision as compared with existing methods.

Bleaching correction for DNA measurements in highly diluted solutions using confocal microscopy.

Determining the concentration of nucleic acids in biological samples precisely and reliably still is a challenge. In particular when only very small sample quantities are available for analysis, the established fluorescence-based methods give insufficient results. Photobleaching is seen as the main reason for this. In this paper we present a method to correct for the photobleaching effect. Using confocal microscopy with single molecule sensitivity, we derived calibration curves from DNA solutions with defined fragment length. We analyzed dilution series over a wide range of concentrations (1 pg/μl-1000 pg/μl) and measured their specific diffusion coefficients employing fluorescence correlation spectroscopy. Using this information, we corrected the measured fluorescence intensity of the calibration solutions for photobleaching effects. We evaluated our method by analyzing a series of DNA mixtures of varying composition. For fragments smaller than 1000 bp, our method allows to determine sample concentrations with high precision in very small sample quantities (< 2 μl with concentrations < 20 pg/μl). Once the technical parameters are determined and remain stable in an established process, our improved calibration method will make measuring molecular biological samples of unknown sequence composition more efficient, accurate and sample-saving than previous methods.

Evolutionary Robot Calibration and Nonlinear Compensation Methodology Based on GA-DNN and an Extra Compliance Error Model

This study addresses the problem of nonlinear error predictive compensation to achieve high positioning accuracy for advanced industrial applications. An improved calibration method based on the generalisation performance evaluation is proposed to enhance the stability and accuracy of robot calibration. With the development of technology, a deep neural network (DNN) optimised by a genetic algorithm (GA) is applied to predict the nonlinear error of the calibrated robot. To address the change of external payload, an extra compliance error model is established with a linear piecewise method. A global compensation method combining the GA-DNN nonlinear regression prediction model and the compliance error model is then proposed to achieve the robot’s high-precision positioning performance under any external payload. Experimental results obtained on a Staubli RX160L robot with a FARO laser tracker are introduced to demonstrate the effectiveness and benefits of our proposed methodology. The enhanced positioning accuracy can reach 0.22 mm with 98% probability (i.e., the maximum positioning error in all test data).

In Situ Measurement of Potassium Release during Biomass Combustion Using Laser-Induced Breakdown Spectroscopy: Effect of Silicate on Potassium Release

In this study, an improved calibration method for the in situ measurement of potassium (K) concentration in the flame field was developed using laser-induced breakdown spectroscopy. The temporal be...

Flexible calibration method for visual measurement using an improved target with vanishing constraints.

In this paper, an improved calibration method based on vanishing constraints is proposed for calculating the extrinsic parameters of cameras. First, we come up with a improved target based on the conventional target with two groups of orthogonal parallel lines. The novel target is composed of two groups of parallel lines with a certain angle range from 80° to 90°, which can reduce the difficulty of target production and the manufacturing cost. Furthermore, in the optimization process, we design a new function with a more robust penalty factor instead of using the experienced values to get the extrinsic parameters for the binocular vision sensors. Finally, on account of using the improved target and the novel optimiazation function, the proposed method is more flexible and robust compared with Zhang's method.

An Improved Method for Extrinsic Calibration of Tilting 2D LRF

This paper proposes an improved calibration method to accurately estimate extrinsic calibration parameters of a tilting 2D Laser Range Finder (LRF). Tilting 2D LRF (a low cost 3D scanner device) with a unidirectional rotating platform has been widely used in robotics applications to scan the 3D environment. Ideally, the tilt axis of rotating mechanism should pass through the optical rotation centre of the 2D LRF. However, due to misalignment during assembling of 2D LRF with the rotating platform, the centres of rotation may not coincide with each other. Though, the system must be calibrated to align both the centres of rotation so as to improve the accuracy in building 3D point cloud of the environment. Unlike the previous calibration techniques, the main advantage of the proposed method is that it accurately estimates all 6-DOF calibration parameters, especially rotation and translation calibration parameters along motor rotation axis between 2D LRF and rotating platform without any additional hardware, camera or rolling/bidirectional rotation mechanism. The proposed method utilizes the normal vector to the calibration board plane and coordinates of laser points at the endpoints of the extracted calibration board line in the 2D scan to obtain these remaining calibration parameters. The obtained parameters are then refined using Levenberg-Marquardt non-linear optimization algorithm. The performance of the algorithm is validated on a range of real as well as synthetic data and the estimated parameters with the proposed approach exhibits 24.54% reduction in RMS (root mean square) error as compared to the conventional approach. Furthermore, qualitative and quantitative analysis shows that the proposed method produces accurate results and is able to reduce the artifacts along the rotation axis in the 3D point cloud which usually appear in the point cloud obtained from the conventional approach.

Single-step calibration method for nano indentation testing machines

Nano indentation is an effective method for materials mechanical characterisation at grain scale. Literature underlined relevance of testing machine calibration to measurement uncertainty of the mechanical characterisation. ISO 14577-2 defines multi-step iterative methods for calibrating frame compliance and indenter area function that do not require high-resolution microscopes. Previous research demonstrated that standard's recommendations are unsatisfactory and result in high calibration uncertainty. This work defines an improved calibration method based on a single-step procedure that achieves, as proved by experimental tests, definite advantages in terms of implementation and measurement uncertainty of both calibration and mechanical characterisation with respect to current procedures.

Improved Calibration Method for Resistive Sensors Using Direct Interface Circuits

Traditional calibration methods for measuring resistance values using a direct interface circuit, comprising a capacitor and some calibration resistors, offer a straightforward, economical option. However, such methods show greater inaccuracies as resistance values decrease. This article presents a modification of the method that ensures more accurate measurements and extends the range of resistance values that can be measured. Unlike the linear equation used in the traditional method, the proposed method obtains the power functions related to resistance value and measured discharge time. Since these circuits need calibration resistors, criteria are established to find their values. To reduce arithmetical complexity, two approximations are tested to calculate the exact value of the resistance. With this approach, the relative errors for low resistances are reduced and the measuring range is extended. Three measurement setups were carried out with a microcontroller and a field-programmable gate array (FPGA) to validate the results, showing the validity of the method independently of the device. Using the FPGA configured so that the maximum current that can be sink per output pin is 24 mA, the error in the estimation of a resistance of $9.9~\Omega $ is ten times less than that obtained using the classic two-point calibration method.

Improved calibration method based on the RANSAC approach and an improved gray centroid method for a laser-line-based structured light system.

This paper proposes an improved calibration method for a structured light system by using the random sample consensus (RANSAC) method with nonlinear optimization and an improved gray centroid method. The proposed method is composed of two steps: calibrating intrinsic and extrinsic parameters for the camera, exploiting the improved gray centroid method to extract the centerline, and fitting the structured light plane by the RANSAC approach with the three-dimensional (3D) points obtained from different positions. The error function caused by the extracted centerline is deduced based on the pixel error perturbation method. The error results of the 3D points are simulated and analyzed. An imaging system is built to realize the 3D imaging. The experimental results show that the calibration error is within 0.08 mm and the reconstruction error is less than 0.45 mm. Moreover, it performs better for the reconstruction of complex objects compared with traditional methods.