scholarly journals Global Calibration Method of a Camera Using the Constraint of Line Features and 3D World Points

2016 ◽  
Vol 16 (4) ◽  
pp. 190-196 ◽  
Author(s):  
Guan Xu ◽  
Xinyuan Zhang ◽  
Xiaotao Li ◽  
Jian Su ◽  
Zhaobing Hao

Abstract We present a reliable calibration method using the constraint of 2D projective lines and 3D world points to elaborate the accuracy of the camera calibration. Based on the relationship between the 3D points and the projective plane, the constraint equations of the transformation matrix are generated from the 3D points and 2D projective lines. The transformation matrix is solved by the singular value decomposition. The proposed method is compared with the point-based calibration to verify the measurement validity. The mean values of the root-mean-square errors using the proposed method are 7.69×10−4, 6.98×10−4, 2.29×10−4, and 1.09×10−3 while the ones of the original method are 8.10×10−4, 1.29×10−2, 2.58×10−2, and 8.12×10−3. Moreover, the average logarithmic errors of the calibration method are evaluated and compared with the former method in different Gaussian noises and projective lines. The variances of the average errors using the proposed method are 1.70×10−5, 1.39×10−4, 1.13×10−4, and 4.06×10−4, which indicates the stability and accuracy of the method.

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. C239-C249
Author(s):  
Song Xu ◽  
Xiaoming Tang ◽  
Yuanda Su

Accurate modeling of elastic properties of cracked rocks in the earth’s shallow crust has long been an important topic in the field of geophysics. A sphere-equivalency approach of elastic wave scattering was used to model the elastic moduli of an isotropic solid containing aligned cracks. The results were compared with those of the existing Eshelby-Cheng and Hudson’s theories for dry and fluid saturation conditions, showing remarkably improved stability and accuracy for high crack concentrations, especially for Hudson’s second-order model. The stability and accuracy of the new approach were determined for varying solid and crack parameters. Finally, the new and existing theories were applied to model the laboratory ultrasonic experimental data measured on artificially cracked samples with varying wave frequencies and crack concentrations. Compared to Hudson’s theory, the new model agrees significantly better with the data. Specifically, the root-mean-square errors of theoretical fitting to data from our model are generally smaller than those from the other two models. We have thus developed an effective tool for modeling elastic properties of cracked rocks.


2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xiaoyan Chen ◽  
Qiuju Zhang ◽  
Yilin Sun

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).


2013 ◽  
Vol 10 (03) ◽  
pp. 1350009 ◽  
Author(s):  
REZA POURGHOLI ◽  
AMIN ESFAHANI

In this paper, we will first study the existence and uniqueness of the solution of a one-dimensional inverse problem for an inhomogeneous linear wave equation with initial and boundary conditions via an auxiliary problem. Then a stable numerical method consisting of zeroth-, first-, and second-order Tikhonov regularization to the matrix form of Duhamel's principle for solving this inverse problem is presented. The stability and accuracy of the scheme presented is evaluated by comparison with the Singular Value Decomposition method. Some numerical experiments confirm the utility of this algorithm as the results are in good agreement with the exact data.


Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2830
Author(s):  
Sili Wang ◽  
Mark P. Panning ◽  
Steven D. Vance ◽  
Wenzhan Song

Locating underground microseismic events is important for monitoring subsurface activity and understanding the planetary subsurface evolution. Due to bandwidth limitations, especially in applications involving planetarily-distributed sensor networks, networks should be designed to perform the localization algorithm in-situ, so that only the source location information needs to be sent out, not the raw data. In this paper, we propose a decentralized Gaussian beam time-reverse imaging (GB-TRI) algorithm that can be incorporated to the distributed sensors to detect and locate underground microseismic events with reduced usage of computational resources and communication bandwidth of the network. After the in-situ distributed computation, the final real-time location result is generated and delivered. We used a real-time simulation platform to test the performance of the system. We also evaluated the stability and accuracy of our proposed GB-TRI localization algorithm using extensive experiments and tests.


Robotica ◽  
2021 ◽  
pp. 1-22
Author(s):  
Zhouxiang Jiang ◽  
Min Huang

SUMMARY In typical calibration methods (kinematic or non-kinematic) for serial industrial robot, though measurement instruments with high resolutions are adopted, measurement configurations are optimized, and redundant parameters are eliminated from identification model, calibration accuracy is still limited under measurement noise. This might be because huge gaps still exist among the singular values of typical identification Jacobians, thereby causing the identification models ill conditioned. This paper addresses such problem by using new identification models established in two steps. First, the typical models are divided into the submodels with truncated singular values. In this way, the unknown parameters corresponding to the abnormal singular values are removed, thereby reducing the condition numbers of the new submodels. However, these models might still be ill conditioned. Therefore, the second step is to further centralize the singular values of each submodel by using a matrix balance method. Afterward, all submodels are well conditioned and obtain much higher observability indices compared with those of typical models. Simulation results indicate that significant improvements in the stability of identification results and the identifiability of unknown parameters are acquired by using the new identification submodels. Experimental results indicate that the proposed calibration method increases the identification accuracy without incurring additional hardware setup costs to the typical calibration method.


Author(s):  
Weitao Chen ◽  
Shenhai Ran ◽  
Canhui Wu ◽  
Bengt Jacobson

AbstractCo-simulation is widely used in the industry for the simulation of multidomain systems. Because the coupling variables cannot be communicated continuously, the co-simulation results can be unstable and inaccurate, especially when an explicit parallel approach is applied. To address this issue, new coupling methods to improve the stability and accuracy have been developed in recent years. However, the assessment of their performance is sometimes not straightforward or is even impossible owing to the case-dependent effect. The selection of the coupling method and its tuning cannot be performed before running the co-simulation, especially with a time-varying system.In this work, the co-simulation system is analyzed in the frequency domain as a sampled-data interconnection. Then a new coupling method based on the H-infinity synthesis is developed. The method intends to reconstruct the coupling variable by adding a compensator and smoother at the interface and to minimize the error from the sample-hold process. A convergence analysis in the frequency domain shows that the coupling error can be reduced in a wide frequency range, which implies good robustness. The new method is verified using two co-simulation cases. The first case is a dual mass–spring–damper system with random parameters and the second case is a co-simulation of a multibody dynamic (MBD) vehicle model and an electric power-assisted steering (EPAS) system model. Experimental results show that the method can improve the stability and accuracy, which enables a larger communication step to speed up the explicit parallel co-simulation.


2021 ◽  
Vol 11 (5) ◽  
pp. 2098
Author(s):  
Heyi Wei ◽  
Wenhua Jiang ◽  
Xuejun Liu ◽  
Bo Huang

Knowledge of the sunshine requirements of landscape plants is important information for the adaptive selection and configuration of plants for urban greening, and is also a basic attribute of plant databases. In the existing studies, the light compensation point (LCP) and light saturation point (LSP) have been commonly used to indicate the shade tolerance for a specific plant; however, these values are difficult to adopt in practice because the landscape architect does not always know what range of solar radiation is the best for maintaining plant health, i.e., normal growth and reproduction. In this paper, to bridge the gap, we present a novel digital framework to predict the sunshine requirements of landscape plants. First, the research introduces the proposed framework, which is composed of a black-box model, solar radiation simulation, and a health standard system for plants. Then, the data fitting between solar radiation and plant growth response is used to obtain the value of solar radiation at different health levels. Finally, we adopt the LI-6400XT Portable Photosynthetic System (Li-Cor Inc., Lincoln, NE, USA) to verify the stability and accuracy of the digital framework through 15 landscape plant species of a residential area in the city of Wuhan, China, and also compared and analyzed the results of other researchers on the same plant species. The results show that the digital framework can robustly obtain the values of the healthy, sub-healthy, and unhealthy levels for the 15 landscape plant species. The purpose of this study is to provide an efficient forecasting tool for large-scale surveys of plant sunshine requirements. The proposed framework will be beneficial for the adaptive selection and configuration of urban plants and will facilitate the construction of landscape plant databases in future studies.


Electronics ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 333
Author(s):  
Jian Le ◽  
Hao Zhang ◽  
Cao Wang ◽  
Xingrui Li ◽  
Jiangfeng Zhu

To enhance the stability and accuracy of the digital-physical hybrid simulation system of a modular multilevel converter-based high voltage direct current (MMC-HVDC) system, this paper presents an improved power interface modeling algorithm based on ideal transformer method (ITM). By analyzing the stability condition of a hybrid simulation system based on the ITM model, the current of a so-called virtual resistance is added to the control signal of the controlled current source in the digital subsystem, and the stability of the hybrid simulation system with the improved power interface model is analyzed. The value of the virtual resistance is optimized by comprehensively considering system stability and simulation precision. A two-terminal bipolar MMC-HVDC simulation system based on the proposed power interface model is established. The comparisons of the simulation results verify that the proposed method can effectively improve the stability of the hybrid simulation system, and at the same time has the advantages of high simulation accuracy and easy implementation.


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