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Issues per year: 4
Current issue: Feb 2024
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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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  1/2012 - 10

 HIGH-IMPACT PAPER 

A Motion Planning System for Mobile Robots

TUNCER, A. See more information about TUNCER, A. on SCOPUS See more information about TUNCER, A. on IEEExplore See more information about TUNCER, A. on Web of Science, YILDIRIM, M. See more information about  YILDIRIM, M. on SCOPUS See more information about  YILDIRIM, M. on SCOPUS See more information about YILDIRIM, M. on Web of Science, ERKAN, K. See more information about ERKAN, K. on SCOPUS See more information about ERKAN, K. on SCOPUS See more information about ERKAN, K. on Web of Science
 
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Download PDF pdficon (855 KB) | Citation | Downloads: 1,672 | Views: 5,151

Author keywords
genetic algorithm, mobile robot, motion planning

References keywords
robot(12), genetic(12), planning(10), path(9), mobile(8), algorithm(8), algorithms(6), robotics(5), autonomous(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2012-02-28
Volume 12, Issue 1, Year 2012, On page(s): 57 - 62
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.01010
Web of Science Accession Number: 000301075000010
SCOPUS ID: 84860754571

Abstract
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Full text preview
In this paper, a motion planning system for a mobile robot is proposed. Path planning tries to find a feasible path for mobile robots to move from a starting node to a target node in an environment with obstacles. A genetic algorithm is used to generate an optimal path by taking the advantage of its strong optimization ability. Mobile robot, obstacle and target localizations are realized by means of camera and image processing. A graphical user interface (GUI) is designed for the motion planning system that allows the user to interact with the robot system and to observe the robot environment. All the software components of the system are written in MATLAB that provides to use non-predefined accessories rather than the robot firmware has, to avoid confusing in C++ libraries of robot's proprietary software, to control the robot in detail and not to re-compile the programs frequently in real-time dynamic operations.


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

[1] Y. Hu and S. X. Yang, "A knowledge based genetic algorithm for path planning of a mobile robot," Proceedings of the 2004 IEEE, Int. Conf. on Robotics & Automation, Vol. 5, pp. 4350-4355, 2004.
[CrossRef]


[2] J. Tu and S. X. Yang, "Genetic algorithm based path planning for a mobile robot," Robotics and Automation. Proceedings. ICRA '03. IEEE Int Conf. on, Vol. 1, pp. 1221-1226, 2003.
[CrossRef]


[3] I. Al-Taharwa, A. Sheta and M. Al-Weshah, "A mobile robot path planning using genetic algorithm in static environment," J of Computer Science, Vol. 4, pp. 341-344, 2008.
[CrossRef] [SCOPUS Times Cited 216]


[4] A. Elshamli, H. A. Abdullah and S. Areibi, "Genetic algorithm for dynamic path planning," Electrical and Computer Engineering, Canadian Conference on, Vol. 2, pp. 677-680, 2004.
[CrossRef]


[5] S. M. H. Nabavi, A. Kazemi and M. A. S. Masoum, "Social welfare improvement by TCSC using real code based genetic algorithm in double-sided auction market," Advances in Electrical and Computer Engineering, Vol. 11, pp. 99-106, 2011.
[CrossRef] [Full Text] [Web of Science Times Cited 7] [SCOPUS Times Cited 11]


[6] H. J. Chang, C. S. G. Lee, Yung-Hsiang Lu, Y. C. Hu, "P-SLAM: simultaneous localization and mapping with environmental-structure prediction," IEEE Transactions on Robotics, Vol. 23, No. 2, pp.281-293,2007.
[CrossRef] [Web of Science Times Cited 46] [SCOPUS Times Cited 61]


[7] Y. Zhuang, M. Gu, W. Wang and H. Yu, "Multi-robot cooperative localization based on autonomous motion state estimation and laser data interaction," Science China Information Sciences, Vol. 53, No. 11, pp. 2240-2250, 2010.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 17]


[8] H. Teimoori and A. V. Savkin, "Equiangular navigation and guidance of a wheeled mobile robot based on range-only measurements," Robotics and Autonomous Systems, Vol. 58, pp. 203-215, 2010.
[CrossRef] [Web of Science Times Cited 56] [SCOPUS Times Cited 71]


[9] A. Yufka, O. Parlaktuna, "Performance comparison of bug algorithms for mobile robots," 5th International Advanced Technologies Symposium (IATS'09), Karabuk, Turkey, May 13-15, 2009.

[10] [Online] Available: Temporary on-line reference link removed - see the PDF document

[11] [Online] Available: Temporary on-line reference link removed - see the PDF document

[12] [Online] Available: Temporary on-line reference link removed - see the PDF document

[13] Pioneer 3 Operations Manual, Version 6, MobileRobots Inc., September 2010.

[14] T. W. Manikas, K. Ashenayi and R. L. Wainwright, "Genetic algorithms for autonomous robot navigation," Instrumentation & Measurement Magazine, IEEE, Vol. 10, pp. 26-31, 2007.
[CrossRef] [Web of Science Times Cited 76] [SCOPUS Times Cited 105]


[15] M. Naderan-Tahan and M. T. Manzuri-Shalmani, "Efficient and safe path planning for a mobile robot using genetic algorithm," Evolutionary Computation, CEC '09. IEEE Congress on, pp. 2091-2097, 2009.
[CrossRef] [Web of Science Times Cited 18] [SCOPUS Times Cited 21]


[16] Z. Yao and L. Ma, "A static environment-based path planning method by using genetic algorithm," Computing, Control and Industrial Engineering (CCIE), 2010 International Conference on, Vol. 2, pp. 405-407, 2010.
[CrossRef] [SCOPUS Times Cited 21]


[17] Q. Li, W. Zhang, Y. Yin, Z. Wang and G. Liu, "An improved genetic algorithm of optimum path planning for mobile robots," Intelligent Systems Design and Applications, ISDA '06. Sixth International Conference on, Vol. 2, pp. 637-642, 2006.
[CrossRef] [SCOPUS Times Cited 54]


[18] E. Gelenbe, P. Liu and J. Laine, "Genetic algorithms for route discovery," Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, Vol. 36, pp. 1247-1254, 2006.
[CrossRef] [Web of Science Times Cited 51] [SCOPUS Times Cited 61]


[19] K. Sugihara and J. Smith, "Genetic algorithms for adaptive motion planning of an autonomous mobil robot," Computational Intelligence in Robotics and Automation, CIRA'97, Proceedings, IEEE International Symposium on, pp. 138-143, 1997.
[CrossRef] [Web of Science Times Cited 94]


[20] G. Nagib and W. Gharieb, "Path planning for a mobile robot using genetic algorithms," Electrical, Electronic and Computer Engineering, ICEEC '04, International Conference on, pp. 185-189, 2004.
[CrossRef] [Web of Science Times Cited 32]


[21] E. Masehian and D. Sedighizadeh, "Multi-objective PSO- and NPSO-based algorithms for robot path planning," Advances in Electrical and Computer Engineering, Vol. 10, pp. 69-76, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 52] [SCOPUS Times Cited 65]


References Weight

Web of Science® Citations for all references: 447 TCR
SCOPUS® Citations for all references: 703 TCR

Web of Science® Average Citations per reference: 21 ACR
SCOPUS® Average Citations per reference: 33 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 2024-03-27 18:20 in 101 seconds.




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


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