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JCR Impact Factor: 0.650
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PUBLISHER

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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LATEST NEWS

2019-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2018. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.650, and the JCR 5-Year Impact Factor is 0.639.

2018-May-31
Starting today, the minimum number a pages for a paper is 8, so all submitted papers should have 8, 10 or 12 pages. No exceptions will be accepted.

2018-Jun-27
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2017-Jun-14
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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
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,396 KB) | Citation | Downloads: 443 | Views: 1,220

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), localization(5), laser(5), automation(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

[1] T. Bailey, H. Durrant-Whyte, "Simultaneous localization and mapping (SLAM): Part II", IEEE Robotics and Automation Magazine, vol. 13, no. 3, pp. 108-117. 2006.
[CrossRef] [Web of Science Times Cited 776] [SCOPUS Times Cited 1131]


[2] J. Gutmann, T. Weigel, B. Nebel, "A fast, accurate and robust method for self-localization in polygonal environments using laser range finders", Advanced Robotics, vol. 14, no. 8, pp. 651-667 2001.
[CrossRef] [Web of Science Times Cited 36] [SCOPUS Times Cited 51]


[3] W. Hao, Y. Wang, X. Ning, M. Zhao, J. Zhang, Z. Shi, X. Zhang, "Automatic building extraction from terrestrial laser scanning data," Advances in Electrical and Computer Engineering, vol.13, no.3, pp.11-16, 2013.
[CrossRef] [Full Text] [Web of Science Times Cited 7] [SCOPUS Times Cited 8]


[4] X. Ning, Y. Wang, "Object extraction from architecture scenes through 3d local scanned data analysis," Advances in Electrical and Computer Engineering, vol.12, no.3, pp.73-78, 2012.
[CrossRef] [Full Text] [Web of Science Times Cited 2] [SCOPUS Times Cited 3]


[5] S. Bando, T. Tsubouchi, S. Yuta, "Scan matching method using projection in dominant direction of indoor environment", Advanced Robotics, vol. 28, no. 18, pp. 1243-1251. 2014.
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 2]


[6] M. Ahmad Sharbafi, S. Taleghani, E. Esmaeili, "ICE matching, robust and fast feature-based scan matching for an online operation", Journal of Experimental and Theoretical Artificial Intelligence, vol. 27, no. 2, pp. 137-157. 2015.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]


[7] R. Lindenbergh, P. Pietrzyk, "Change detection and deformation analysis using static and mobile laser scanning." Applied Geomatics, 7(2), pp. 65-74. 2015.
[CrossRef] [Web of Science Times Cited 28] [SCOPUS Times Cited 39]


[8] S. Zeng, "A tracking system of multiple LiDAR sensors using scan point matching", IEEE Transactions on Vehicular Technology, vol. 62, no. 6, pp. 2413-2420. 2013.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 6]


[9] G. Zhang, I. H. Suh, "A vertical and floor line-based monocular SLAM system for corridor environments." International Journal of Control, Automation and Systems, vol. 10, no. 3, pp. 547-557, 2012.
[CrossRef] [Web of Science Times Cited 13] [SCOPUS Times Cited 14]


[10] C. Ulas, H. Temeltas, "A fast and robust feature-based scan-matching method in 3d slam and the effect of sampling strategies", International Journal of Advanced Robotic Systems, vol. 10, no. 1, 2013.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 9]


[11] A. Fernando, Auat Cheein, Ricardo Carelli, "Analysis of different feature selection criteria based on a covariance convergence perspective for a slam algorithm." Sensors, vol. 11, pp. 62-89, 2011.
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 14]


[12] E. Tsardoulias, L. Petrou, "Critical rays scan match SLAM", Journal of Intelligent and Robotic Systems: Theory and Applications, vol. 72, no. 3-4, pp. 441-462. 2013.
[CrossRef] [Web of Science Times Cited 20] [SCOPUS Times Cited 22]


[13] D. Z. Wang, I. Posner, P. Newman, "Model-free detection and tracking of dynamic objects with 2D LIDAR", International Journal of Robotics Research, vol. 34, no. 7, pp. 1039-1063. 2015.
[CrossRef]


[14] R. Guo, F. Sun, L. Yuan, "ICP based on polar point matching with application to graph-SLAM", 2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009, pp. 1122. 2009.
[CrossRef] [SCOPUS Times Cited 10]


[15] M. Mirkhani, R. Forsati, A. M. Shahri, A. Moayedikia, "A novel efficient algorithm for mobile robot localization", Robotics and Autonomous Systems, vol. 61, no. 9, pp. 920-931. 2013.
[CrossRef] [Web of Science Times Cited 17] [SCOPUS Times Cited 34]


[16] J. Neira, J. D. Tardos, "Data association in stochastic mapping using the joint compatibility test", IEEE transaction on Robotics and Automation, vol. 17, no. 6, pp. 890-897, 2001.
[CrossRef] [Web of Science Times Cited 393] [SCOPUS Times Cited 520]


[17] Yangming Li, Shuai Li, Quanjun Song, Hai Liu, M. Q. Meng, "Fast and robust data association using posterior based approximate joint compatibility test," IEEE Transactions on Industrial Informatics, vol.10, no.1, pp.331,339, 2014.
[CrossRef] [Web of Science Times Cited 19] [SCOPUS Times Cited 20]


[18] J. Zeng Wen, T. D. Zhang, P. Jiang Da, "Analysis of data association methods of SLAM", Journal of Systems Engineering and Electronics, ISSN: 1001-506X, vol. 32, no. 4, pp. 860-864, 2010

[19] A. Diosi, L. Kleeman, "Laser scan matching in polar coordinates with application to SLAM", 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, pp. 1439, 2005.
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 118]


[20] D. Spelic, F. Novak, B. Zalik, "A fast method for the alignment of the displacement of voxel data," Advances in Electrical and Computer Engineering, vol. 12, no. 2, pp. 41-46, 2012.
[CrossRef] [Full Text] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]


[21] M. Choi, J. Choi, W. K. Chung, "Correlation-based scan matching using ultrasonic sensors for EKF localization", Advanced Robotics, vol. 26, no. 13, pp. 1495-1519. 2012.
[CrossRef] [Web of Science Times Cited 10] [SCOPUS Times Cited 12]


[22] Davor Graovac, Srecko Juric-Kavelj, Ivan Petrovic, "Mobile robot pose tracking by correlation of laser range finder scans in Hough domain.", 19th International Workshop on Robotics in Alpe-Adria-Danube Region - RAAD2010, 2010.
[CrossRef] [SCOPUS Times Cited 8]


[23] K. Briechle, U. D. Hanebeck, "Self-localization of a mobile robot using fast normalized cross correlation," IEEE International Conference on Systems, Man, and Cybernetics, IEEE SMC '99 Conference Proceedings. vol. 4, no. 1, pp.720-725, 1999.
[CrossRef]


[24] Lei Zhang, Sung-In Choi, Soon-Yong Park, "Polar-Cartesian hybrid transforms: a novel 2d range scan registration algorithm", International Journal of Control, Automation, and Systems, vol. 11, no. 5, pp. 1001-1008, 2013.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 5]


[25] M. Altermatt, A. Martinelli, N. Tomatis, R. Siegwart, "SLAM with corner features based on a relative map". 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), vol. 2, pp. 1053-1058, 2004.
[CrossRef]


[26] T. Chai, R. R. Draxler, "Root mean square error (RMSE) or mean absolute error (MAE)? - arguments against avoiding RMSE in the literature," Geosci. Model Dev., vol. 7, pp. 1247-1250, 2014.
[CrossRef] [Web of Science Times Cited 674] [SCOPUS Times Cited 795]




References Weight

Web of Science® Citations for all references: 2,029 TCR
SCOPUS® Citations for all references: 2,823 TCR

Web of Science® Average Citations per reference: 75 ACR
SCOPUS® Average Citations per reference: 105 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 2019-09-12 15:16 in 171 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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