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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Broken Bar Fault Detection in IM Operating Under No-Load Condition, RELJIC, D., JERKAN, D., MARCETIC, D., OROS, D.
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LATEST NEWS

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Apr-04
We have the confirmation Advances in Electrical and Computer Engineering will be included in the EBSCO database.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

2017-Jan-30
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2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

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  4/2016 - 3

A Novel Keep Zero as Zero Polar Correlation Technique for Mobile Robot Localization using LIDAR

SIDHARTHAN, R. K. See more information about SIDHARTHAN, R. K. on SCOPUS See more information about SIDHARTHAN, R. K. on IEEExplore See more information about SIDHARTHAN, R. K. on Web of Science, KANNAN, R. See more information about  KANNAN, R. on SCOPUS See more information about  KANNAN, R. on SCOPUS See more information about KANNAN, R. on Web of Science, SRINIVASAN, S. See more information about  SRINIVASAN, S. on SCOPUS See more information about  SRINIVASAN, S. on SCOPUS See more information about SRINIVASAN, S. on Web of Science, BALAS, M. M. See more information about BALAS, M. M. on SCOPUS See more information about BALAS, M. M. on SCOPUS See more information about BALAS, M. M. on Web of Science
 
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Download PDF pdficon (1,396 KB) | Citation | Downloads: 299 | Views: 394

Author keywords
correlation, mobile robots, pattern matching, sensor fusion, simultaneous localization and mapping

References keywords
systems(9), slam(9), scan(8), robotics(8), matching(8), fast(6), data(6), zhang(5), localization(5), laser(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-11-30
Volume 16, Issue 4, Year 2016, On page(s): 15 - 22
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.04003
Web of Science Accession Number: 000390675900003
SCOPUS ID: 85007524779

Abstract
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Sensor fusion based localization techniques often need accurate estimate of the fast and uncertain scene change in environment. To determine the scene change from two consecutive LIDAR scans, this paper proposes a novel technique called 'keep zero as zero' polar correlation. As it name implies any zero in the scan data is kept isolated from scene change estimation as it do not carry any information about scene change. Unlike existing techniques, the proposed methodology employs minimization of selective horizontal and vertically shifted sum of difference between the scans to estimate scene change in terms of rotation and translation. Minimization of the proposed correlation function across the specified search space can guarantee an accurate estimate of scene change without any ambiguity. The performance of the proposed method is tested experimentally on a mobile robot in two modes depending on the scene change. In the first mode, scene change is detected using dynamic LIDAR, whereas static LIDAR is used in the second mode. The proposed methodology is found to be more robust to environmental uncertainties with a reliable level of localization accuracy.


References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 1,166 TCR
SCOPUS® Citations for all references: 1,776 TCR

Web of Science® Average Citations per reference: 43 ACR
SCOPUS® Average Citations per reference: 66 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2017-07-22 18:53 in 168 seconds.




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