scholarly journals High Precision Positioning with Multi-Camera Setups: Adaptive Kalman Fusion Algorithm for Fiducial Markers

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2746 ◽  
Author(s):  
Dragos Constantin Popescu ◽  
Ioan Dumitrache ◽  
Simona Iuliana Caramihai ◽  
Mihail Octavian Cernaianu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
High Precision ◽  
Measurement Noise ◽  
Fusion Method ◽  
Fiducial Markers ◽  
Multiple Cameras ◽  
Precision Positioning ◽  
Fusion Algorithm ◽  
Physics Experiments

The paper addresses the problem of fusing the measurements from multiple cameras in order to estimate the position of fiducial markers. The objectives are to increase the precision and to extend the working area of the system. The proposed fusion method employs an adaptive Kalman algorithm which is used for calibrating the setup of cameras as well as for estimating the pose of the marker. Special measures are taken in order to mitigate the effect of the measurement noise. The proposed method is further tested in different scenarios using a Monte Carlo simulation, whose qualitative precision results are determined and compared. The solution is designed for specific positioning and alignment tasks in physics experiments, but also, has a degree of generality that makes it suitable for a wider range of applications.

scholarly journals Determination of electron backscattering coefficient of beryllium by a high-precision Monte Carlo simulation

2021 ◽  
Vol 26 ◽  
pp. 100862
Author(s):  
Abrar Hussain ◽  
Lihao Yang ◽  
Shifeng Mao ◽  
Bo Da ◽  
Károly Tőkési ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
High Precision ◽  
Backscattering Coefficient ◽  
Electron Backscattering

scholarly journals ANALYSIS OF RANDOM NUMBER GENERATORS USING MONTE CARLO SIMULATION

1994 ◽  
Vol 05 (03) ◽  
pp. 547-560 ◽  
Author(s):  
P.D. CODDINGTON
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Ising Model ◽  
High Precision ◽  
Random Number ◽  
Statistical Tests ◽  
Exact Results ◽  
Random Number Generators ◽  
Monte Carlo Algorithms

Monte Carlo simulation is one of the main applications involving the use of random number generators. It is also one of the best methods of testing the randomness properties of such generators, by comparing results of simulations using different generators with each other, or with analytic results. Here we compare the performance of some popular random number generators by high precision Monte Carlo simulation of the 2-d Ising model, for which exact results are known, using the Metropolis, Swendsen-Wang, and Wolff Monte Carlo algorithms. Many widely used generators that perform well in standard statistical tests are shown to fail these Monte Carlo tests.

Covariance Intersection Fusion Kalman Estimators

2011 ◽  
Vol 121-126 ◽  
pp. 750-754
Author(s):  
Yuan Gao ◽  
Zi Li Deng
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Fusion Algorithm ◽  
Cross Covariance ◽  
Covariance Intersection ◽  
Monte Carlo Simulation Result ◽  
Innovation Model ◽  
Actual Accuracy

By the CI (Covariance Intersection) fusion algorithm, based on the ARMA innovation model, the two-sensor CI fusion Kalman estimators are presented for the systems with unknown cross-covariance. It is proved that their estimation accuracies are higher than those of the local Kalman estimators, and are lower than those of the optimal fused Kalman estimators. A Monte-Carlo simulation result shows that the actual accuracy of the presented CI fusion Kalman estimator are close to those of the optimal fused Kalman estimators with known cross-covariance.

scholarly journals Optimizing the Calibration Error of Refraction Angles in Ultrasonic Angle Beam Testing

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1427
Author(s):  
Zhihui Cai ◽  
Zhangmin Jin ◽  
Linyi Zhu ◽  
Yuebing Li ◽  
Yuebao Lei ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Probability Distribution ◽  
Data Fusion ◽  
Ultrasonic Testing ◽  
Calibration Error ◽  
Fusion Method ◽  
Refraction Angle ◽  
Calibration Process ◽  
Mechanical Components

Ultrasonic testing is a useful approach for quantifying the flaws in mechanical components. The height of the flaws in ultrasonic angle beam testing is closely related to the calibration value of the probe refraction angle. In order to reduce the calibration error, some ignored data during the traditional calibration process are reanalyzed and fused to determine the refraction angle. Both arithmetical measurement fusion method and weighted measurement fusion method are applied and compared. Monte Carlo simulation is used to estimate the probability distribution of the refraction angle and obtain the optimal refraction angle weights. Experiments were carried out to verify the results of Monte Carlo simulation. The applicability of data fusion on refraction angles is investigated. It was found in the study that the data fused with the refraction angle is helpful for measuring the height of flaws.

scholarly journals Small-Range High-Precision Positioning Based on Two-Point Coordination for Robot

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Zhengping Li ◽  
Chaoliang Qin ◽  
Hao Shi
Keyword(s):  
High Precision ◽  
Sampling Frequency ◽  
Small Range ◽  
Precision Positioning ◽  
Fusion Algorithm ◽  
Positioning Accuracy ◽  
Sinc Interpolation ◽  
Rms Error ◽  
Simulation Results ◽  
Positioning Algorithm

This paper proposed a two-point coordinated positioning algorithm. Based on the assumption that the distance between two points was constant, a fusion algorithm was introduced into the positioning process to enhance the positioning accuracy. The simulation results showed that the proposed algorithm could reduce the RMS error to about 50% of the improved sinc interpolation-based positioning algorithm when the sampling frequency was 500 MHz and the interpolation number was 19.

Evaluation of the dose perturbation around gold and steel fiducial markers in a medical linac through Geant4 Monte Carlo simulation

2015 ◽  
Vol 23 (2) ◽  
pp. 135-140 ◽  
Author(s):  
Antonio Pontoriero ◽  
Ernesto Amato ◽  
Giuseppe Iatí ◽  
Costantino De Renzis ◽  
Stefano Pergolizzi
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Fiducial Markers ◽  
Dose Perturbation ◽  
Geant4 Monte Carlo Simulation ◽  
Medical Linac
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