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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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  2/2016 - 4

 HIGHLY CITED PAPER 

Stochastic Wheel-Slip Compensation Based Robot Localization and Mapping

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, V. E. See more information about BALAS, V. E. on SCOPUS See more information about BALAS, V. E. on SCOPUS See more information about BALAS, V. E. on Web of Science
 
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Download PDF pdficon (853 KB) | Citation | Downloads: 1,005 | Views: 2,911

Author keywords
error compensation, Gaussian processes, mobile robots, motion estimation, simultaneous localization and mapping

References keywords
systems(9), robot(8), robots(7), mobile(7), system(6), vehicle(5), localization(5), intelligent(5), compensation(5), slip(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-05-31
Volume 16, Issue 2, Year 2016, On page(s): 25 - 32
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.02004
Web of Science Accession Number: 000376996100004
SCOPUS ID: 84974839110

Abstract
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Full text preview
Wheel slip compensation is vital for building accurate and reliable dead reckoning based robot localization and mapping algorithms. This investigation presents stochastic slip compensation scheme for robot localization and mapping. Main idea of the slip compensation technique is to use wheel-slip data obtained from experiments to model the variations in slip velocity as Gaussian distributions. This leads to a family of models that are switched depending on the input command. To obtain the wheel-slip measurements, experiments are conducted on a wheeled mobile robot and the measurements thus obtained are used to build the Gaussian models. Then the localization and mapping algorithm is tested on an experimental terrain and a new metric called the map spread factor is used to evaluate the ability of the slip compensation technique. Our results clearly indicate that the proposed methodology improves the accuracy by 72.55% for rotation and 66.67% for translation motion as against an uncompensated mapping system. The proposed compensation technique eliminates the need for extro receptive sensors for slip compensation, complex feature extraction and association algorithms. As a result, we obtain a simple slip compensation scheme for localization and mapping.


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

[1] Jaewon Seo, Hyung Keun Lee, Jang Gyu Lee, Chan Gook Park, "Lever arm compensation for GPS/INS/odometer integrated system", International Journal of Control, Automation, and Systems, vol. 4, no. 2, pp. 247-254, April 2006,
[CrossRef]


[2] R. E. Precup, T. Haidegger, L. Kovacs, "Stable hybrid fuzzy controller-based architecture for robotic telesurgery systems", International Journal of Computational Intelligence and Pattern Recognition (Columbia International Publishing) ISSN 0218-0014, vol. 1, no. 1, pp. 61-76, 2014

[3] A. Tuncer, M. Yildirim, K. Erkan, "A motion planning system for mobile robots," Advances in Electrical and Computer Engineering, vol.12, no.1, pp.57-62, 2012,
[CrossRef] [Full Text] [Web of Science Times Cited 9]


[4] C. Purcaru, R. -E. Precup, D. Iercan, L.-O. Fedorovici, R. -C. David, F. Drãgan, "Optimal robot path planning using gravitational search algorithm", International Journal of Artificial Intelligence (CESER Publications), vol. 10, no. S13, pp. 1-20, 2013

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[CrossRef] [Web of Science Times Cited 10]


[6] S. Srinivasan and R. Ayyagari, "Consensus algorithm for robotic agents over packet dropping links", 3rd International Conference on Biomedical Engineering and Informatics (BMEI), Yantai, pp. 2636-2640, 2010,
[CrossRef]


[7] Silas F. R. Alves, Joao M. Rosario, Humberto Ferasoli Filho, Liz K. A. Rincon and Rosana A. T. Yamasaki, "Conceptual bases of robot navigation modeling, control and applications", Advances in Robot Navigation, ISBN: 978-953-307-346-0, InTech, 2011,
[CrossRef]


[8] Rached Dhaouadi, Ahmad Abu Hatab, "Dynamic modelling of differential-drive mobile robots using Lagrange and Newton-Euler methodologies: a unified framework", Dhaouadi and Hatab, Adv Robot Autom 2013, 2:2,
[CrossRef]


[9] E. I. Laftchiev, C. M. Lagoa, S. N. Brennan, "Vehicle localization using in-vehicle pitch data and dynamical models," IEEE Transactions on Intelligent Transportation Systems, vol.16, no.1, pp.206,220, Feb. 2015,
[CrossRef] [Web of Science Times Cited 31]


[10] Kichun Jo, Keounyup Chu, Myoungho Sunwoo, "Interacting multiple model filter-based sensor fusion of GPS with in-vehicle sensors for real-time vehicle positioning," IEEE Transactions on Intelligent Transportation Systems, vol.13, no.1, pp.329,343, March 2012,
[CrossRef] [Web of Science Times Cited 197]


[11] C. Pozna, R.-E. Precup, P. Földesi, "A novel pose estimation algorithm for robotic navigation", Robotics and Autonomous Systems (Elsevier Science), vol. 63, pp. 10-21, 2015,
[CrossRef] [Web of Science Times Cited 28]


[12] Z. Duan, Z. Cai, H. Min, "Robust dead reckoning system for mobile robots based on particle filter and raw range scan", Sensors (Switzerland), Vol 14, Iss 9, Pages 16532-16562, 2014,
[CrossRef] [Web of Science Times Cited 10]


[13] Jungwook Han, Jeonghong Park, Taeyun Kim, Jinwhan Kim, "Precision navigation and mapping under bridges with an unmanned surface vehicle", Autonomous Robots, Volume 38, Issue 4 , pp 349-362, 2015,
[CrossRef] [Web of Science Times Cited 41]


[14] N. Y. Ko, T. Kuc, "Fusing range measurements from ultrasonic beacons and a laser range finder for localization of a mobile robot", Sensors (Switzerland), vol. 15, no. 5, pp. 11050-11075, 2015,
[CrossRef] [Web of Science Times Cited 27]


[15] A. W. Reza, T. T. Rui, A. S. Kausar, "An optimized indoor RFID positioning system using 3D mobility pattern," Advances in Electrical and Computer Engineering, vol.14, no.2, pp.23-28, 2014,
[CrossRef] [Full Text] [Web of Science Times Cited 2]


[16] Hyoung-Ki Lee, Kiwan Choi, Jiyoung Park, Yeon-Ho Kim, SeokWon Bang, "Improvement of dead reckoning accuracy of a mobile robot by slip detection and compensation using multiple model approach," Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on, vol., no., pp.1140,1147, 22-26 Sept. 2008.
[CrossRef] [Web of Science Times Cited 9]


[17] J. Jung, H. Lee, H. Myung,"Slip compensation of mobile robots using SVM and IMM", Advances in Intelligent Systems and Computing - Robot Intelligence Technology and Applications 2012, Volume 208, Pages 5-12, 2013,
[CrossRef]


[18] Wei Jia, Xuan Xiao, Zhihong Deng, "Self-calibration of INS/Odometer integrated system via Kalman filter," Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on , vol., no., pp.224,228, 18-20 Oct. 2012
[CrossRef]


[19] Z. A. Deng, Y. Hu, J. Yu, Z. Na, "Extended Kalman filter for real time indoor localization by fusing WiFi and smartphone inertial sensors", Micromachines Vol 6, pp 523-543 2015,
[CrossRef] [Web of Science Times Cited 90]


[20] Hyoungki Lee, Jongdae Jung, Kiwan Choi, Jiyoung Park, Hyun Myung, "Fuzzy-logic-assisted interacting multiple model (FLAIMM) for mobile robot localization", Robotics and Autonomous Systems, Vol 60, Issue 12, pp 1592-1606, 2012,
[CrossRef] [Web of Science Times Cited 20]


[21] D. F. Flippo, D. P. Miller, "Turning efficiency prediction for skid steering via single wheel testing", Journal of Terramechanics, Vol 52, pp 23-29, 2012,
[CrossRef] [Web of Science Times Cited 6]


[22] J. Jia, X. Wu, W. Lv, Y. Wu, "Research on error compensation technology for vehicular dead reckoning system during accelerating or decelerating", Yadian Yu Shengguang/Piezoelectrics and Acoustooptics, Vol 33, Issue 2, pp 210-213, 2011

[23] Carlo Arcelli, Gabriella Sanniti di Baja, "Finding local maxima in a pseudo-Euclidian distance transform", Computer Vision, Graphics, and Image Processing, Vol 43, Issue 3, pp 361-367, 1988,
[CrossRef] [Web of Science Times Cited 72]


[24] Jonah H. Lee, "Statistical modeling and comparison with experimental data of tire-soil interaction for combined longitudinal and lateral slip", Journal of Terramechanics, Vol 58, pp 11-25, 2015,
[CrossRef] [Web of Science Times Cited 9]


[25] So, H.C., Lin, L., "Linear least squares approach for accurate received signal strength based source localization". IEEE Transactions on Signal Processing, Vol 59, Issue 8, pp. 4035-4040, 2011,
[CrossRef] [Web of Science Times Cited 182]




References Weight

Web of Science® Citations for all references: 743 TCR
SCOPUS® Citations for all references: 0

Web of Science® Average Citations per reference: 29 ACR
SCOPUS® Average Citations per reference: 0

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 2024-04-09 19:45 in 125 seconds.




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