The ICP algorithm based on stochastic approach

2021 ◽  
Author(s):  
Sergei Voronin ◽  
Artyom Makovetskii ◽  
Vitaly Kober ◽  
Aleksei Voronin
Keyword(s):  
Stochastic Approach ◽  
Icp Algorithm

LIMITATIONS OF THE STOCHASTIC APPROACH IN TWO-PHASE TURBULENT FLOW CALCULATIONS

1996 ◽  
Vol 6 (2) ◽  
pp. 211-225 ◽  
Author(s):  
Keh-Chin Chang ◽  
Wen-Jing Wu ◽  
Muh-Rong Wang
Keyword(s):  
Turbulent Flow ◽  
Stochastic Approach ◽  
Two Phase

STOCHASTIC CALCULATION OF LIFETIME PREDICTION FOR COMPONENTS IN METAL STRUCTURES DUE TO THE GROWTH OF MICRODEFECTS

2020 ◽  
Vol 4 (97) ◽  
pp. 69-76
Author(s):  
IGOR N. SILVERSTOV
Keyword(s):  
Fatigue Strength ◽  
Fracture Mechanics ◽  
Stochastic Approach ◽  
Fatigue Curve ◽  
Probability Of Failure ◽  
Lifetime Prediction ◽  
Statistical Distributions ◽  
Metal Structures

A stochastic approach has been developed to evaluate fatigue strength using elements of the fracture mechanics. The article presents a method for determining the initial parameters of statistical distributions. It also considers the method for constructing a fatigue curve for a component of any size and configuration with any given probability of failure.

A stochastic approach to approximate values in cooperative games

2019 ◽  
Vol 279 (1) ◽  
pp. 93-106 ◽  
Author(s):  
Stefano Benati ◽  
Fernando López-Blázquez ◽  
Justo Puerto
Keyword(s):  
Cooperative Games ◽  
Stochastic Approach

scholarly journals From Exploratory Tunnel to Base Tunnel: Hard Rock TBM Performance Prediction by Means of a Stochastic Approach

2020 ◽  
Vol 53 (12) ◽  
pp. 5473-5487 ◽  
Author(s):  
Andrea Rispoli ◽  
Anna Maria Ferrero ◽  
Marilena Cardu
Keyword(s):  
Performance Prediction ◽  
Early Stage ◽  
Tunnel Boring Machine ◽  
Stochastic Approach ◽  
Critical Issue ◽  
Utilization Factor ◽  
Tbm Performance ◽  
Factors Affecting ◽  
Tunnel Section ◽  
Input Variables

AbstractTunnel boring machine (TBM) performance prediction is often a critical issue in the early stage of a tunnelling project, mainly due to the unpredictable nature of some important factors affecting the machine performance. In this regard, deterministic approaches are normally employed, providing results in terms of average values expected for the TBM performance. Stochastic approaches would offer improvement over deterministic methods, taking into account the parameter variability; however, their use is limited, since the level of information required is often not available. In this study, the data provided by the excavation of the Maddalena exploratory tunnel were used to predict the net and overall TBM performance for a 2.96 km section of the Mont Cenis base tunnel by using a stochastic approach. The preliminary design of the TBM cutterhead was carried out. A prediction model based on field penetration index, machine operating level and utilization factor was adopted. The variability of the parameters involved was analysed. A procedure to take into account the correlation between the input variables was described. The probability of occurrence of the outcomes was evaluated, and the total excavation time expected for the tunnel section analysed was calculated.

A hybrid stochastic approach for offline train trajectory reconstruction

2020 ◽  
Author(s):  
Pier Giuseppe Sessa ◽  
Valerio De Martinis ◽  
Axel Bomhauer-Beins ◽  
Ulrich Alois Weidmann ◽  
Francesco Corman
Keyword(s):  
Stochastic Approach ◽  
Trajectory Reconstruction

scholarly journals Estimating intrafraction tumor motion during fiducial-based liver stereotactic radiotherapy via an iterative closest point (ICP) algorithm

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Wu-zhou Li ◽  
Zhi-wen Liang ◽  
Yi Cao ◽  
Ting-ting Cao ◽  
Hong Quan ◽  
...  
Keyword(s):  
Stereotactic Radiotherapy ◽  
Imaging System ◽  
Liver Tumors ◽  
Three Dimensional ◽  
Rigid Motion ◽  
Iterative Closest Point ◽  
Tumor Motion ◽  
Tracking Accuracy ◽  
Icp Algorithm ◽  
Anterior Posterior

Abstract Background Tumor motion may compromise the accuracy of liver stereotactic radiotherapy. In order to carry out a precise planning, estimating liver tumor motion during radiotherapy has received a lot of attention. Previous approach may have difficult to deal with image data corrupted by noise. The iterative closest point (ICP) algorithm is widely used for estimating the rigid registration of three-dimensional point sets when these data were dense or corrupted. In the light of this, our study estimated the three-dimensional (3D) rigid motion of liver tumors during stereotactic liver radiotherapy using reconstructed 3D coordinates of fiducials based on the ICP algorithm. Methods Four hundred ninety-five pairs of orthogonal kilovoltage (KV) images from the CyberKnife stereo imaging system for 12 patients were used in this study. For each pair of images, the 3D coordinates of fiducial markers inside the liver were calculated via geometric derivations. The 3D coordinates were used to calculate the real-time translational and rotational motion of liver tumors around three axes via an ICP algorithm. The residual error was also investigated both with and without rotational correction. Results The translational shifts of liver tumors in left-right (LR), anterior-posterior (AP),and superior-inferior (SI) directions were 2.92 ± 1.98 mm, 5.54 ± 3.12 mm, and 16.22 ± 5.86 mm, respectively; the rotational angles in left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions were 3.95° ± 3.08°, 4.93° ± 2.90°, and 4.09° ± 1.99°, respectively. Rotational correction decreased 3D fiducial displacement from 1.19 ± 0.35 mm to 0.65 ± 0.24 mm (P<0.001). Conclusions The maximum translational movement occurred in the SI direction. Rotational correction decreased fiducial displacements and increased tumor tracking accuracy.

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