An Innovative Monocular Mobile Object Self-localization Approach Based on Ceiling Vision

2021 ◽  
pp. 713-730
Author(s):  
Alfredo Cuzzocrea ◽  
Luca Camilotti ◽  
Enzo Mumolo
Keyword(s):  
Mobile Object ◽  
Ceiling Vision ◽  
Localization Approach

scholarly journals Ceiling-Vision-Based Mobile Object Self-Localization: A Composite Framework

2021 ◽  
Vol 2021 (2) ◽  
pp. 7-15
Author(s):  
Alfredo Cuzzocrea ◽  
Alfredo Cuzzocrea
Keyword(s):  
Mobile Object ◽  
Ceiling Vision

scholarly journals Adaptive Stochastic Filtration Based on the Estimation of the Covariance Matrix of Measurement Noises Using Irregular Accurate Observations

Inventions ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 10
Author(s):  
Sergey Sokolov ◽  
Arthur Novikov ◽  
Marianna Polyakova
Keyword(s):  
Covariance Matrix ◽  
Adaptive Estimation ◽  
Observation System ◽  
Mobile Object ◽  
New Approach ◽  
Measurement Systems ◽  
System Parameters ◽  
Traditional Scheme ◽  
Adaptive Filtration ◽  
Measurement Noises

In measurement systems operating under various disturbances the probabilistic characteristics of measurement noises are usually known approximately. To improve the observation accuracy, a new approach to the Kalman’s filter adaptation is proposed. In this approach, the Covariance Matrix of Measurement Noises (CMMN) is estimated by accurate measurements detected irregularly by the mobile object observation system (from radiofrequency identifiers, etalon reference, fixed points etc.). The problem of adaptive estimation of the observer’s noises covariance matrix in the Kalman filter is solved analytically for two cases: mutual noises correlation, and its absence. The numerical example for adaptive filtration of complexing navigation system parameters of a mobile object using irregular accurate measurements is given to illustrate the effectiveness of the proposed algorithm. Coordinate estimating errors have changed in comparison with the traditional scheme from 100 m to 2 m in latitude, and from 200 m to 1.5 m in longitude.

Localization simulation of forming-induced residual stresses of composite using prescribed boundary

2021 ◽  
pp. 073168442094118
Author(s):  
Qi Wu ◽  
Hongzhou Zhai ◽  
Nobuhiro Yoshikawa ◽  
Tomotaka Ogasawara ◽  
Naoki Morita
Keyword(s):  
Residual Stresses ◽  
Representative Volume Element ◽  
Computational Cost ◽  
Volume Element ◽  
Thermoplastic Composite ◽  
Structural Deformation ◽  
Element Analysis ◽  
Micro Scale ◽  
Representative Volume ◽  
Localization Approach

A novel localization approach that seamlessly bridges the macro- and micro-scale models is proposed and used to model the forming-induced residual stresses within a representative volume element of a fiber reinforced composite. The approach uses a prescribed boundary that is theoretically deduced by integrating the asymptotic expansion of a composite and the equal strain transfer, thus rendering the simulation setting to be easier than conventional approaches. When the localization approach is used for the finite element analysis, the temperature and residual stresses within an ideal cubic representative volume element are precisely simulated, given a sandwiched thermoplastic composite is formed under one-side cooling condition. The simulation results, after being validated, show that the temperature gradient has an impact on the local residual stresses, especially on the in-plane normal stress transverse to the fiber, and consequently, influences the structural deformation. This newly designed localization approach demonstrates the advantages of enhanced precision and reduced computational cost owing to the fast modeling of the finely meshed representative volume element. This is beneficial for a detailed understanding of the actual residual stresses at the micro-scale.

scholarly journals Augmenting Bug Localization with Part-of-Speech and Invocation

2017 ◽  
Vol 27 (06) ◽  
pp. 925-949 ◽  
Author(s):  
Yu Zhou ◽  
Yanxiang Tong ◽  
Taolue Chen ◽  
Jin Han
Keyword(s):  
Software Maintenance ◽  
Large Scale ◽  
Bug Localization ◽  
Bug Reports ◽  
Part Of Speech ◽  
Adaptive Technique ◽  
Bug Report ◽  
Software Maintenance And Evolution ◽  
Speech Features ◽  
Localization Approach

Bug localization represents one of the most expensive, as well as time-consuming, activities during software maintenance and evolution. To alleviate the workload of developers, numerous methods have been proposed to automate this process and narrow down the scope of reviewing buggy files. In this paper, we present a novel buggy source-file localization approach, using the information from both the bug reports and the source files. We leverage the part-of-speech features of bug reports and the invocation relationship among source files. We also integrate an adaptive technique to further optimize the performance of the approach. The adaptive technique discriminates Top 1 and Top N recommendations for a given bug report and consists of two modules. One module is to maximize the accuracy of the first recommended file, and the other one aims at improving the accuracy of the fixed defect file list. We evaluate our approach on six large-scale open source projects, i.e. ASpectJ, Eclipse, SWT, Zxing, Birt and Tomcat. Compared to the previous work, empirical results show that our approach can improve the overall prediction performance in all of these cases. Particularly, in terms of the Top 1 recommendation accuracy, our approach achieves an enhancement from 22.73% to 39.86% for ASpectJ, from 24.36% to 30.76% for Eclipse, from 31.63% to 46.94% for SWT, from 40% to 55% for ZXing, from 7.97% to 21.99% for Birt, and from 33.37% to 38.90% for Tomcat.

Sign in / Sign up

Export Citation Format

Share Document