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Reseach Article

Comparison between Different Meta-Heuristic Algorithms for Path Planning in Robotics

by Yogita Gigras, Nikita Jora, Anuradha Dhull
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 142 - Number 3
Year of Publication: 2016
Authors: Yogita Gigras, Nikita Jora, Anuradha Dhull
10.5120/ijca2016909705

Yogita Gigras, Nikita Jora, Anuradha Dhull . Comparison between Different Meta-Heuristic Algorithms for Path Planning in Robotics. International Journal of Computer Applications. 142, 3 ( May 2016), 6-10. DOI=10.5120/ijca2016909705

@article{ 10.5120/ijca2016909705,
author = { Yogita Gigras, Nikita Jora, Anuradha Dhull },
title = { Comparison between Different Meta-Heuristic Algorithms for Path Planning in Robotics },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 142 },
number = { 3 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 6-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume142/number3/24874-2016909705/ },
doi = { 10.5120/ijca2016909705 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:43:56.592844+05:30
%A Yogita Gigras
%A Nikita Jora
%A Anuradha Dhull
%T Comparison between Different Meta-Heuristic Algorithms for Path Planning in Robotics
%J International Journal of Computer Applications
%@ 0975-8887
%V 142
%N 3
%P 6-10
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Path planning has been a part of research from a decade and has been evolving with use of several heuristic as well as meta-heuristic techniques. In this paper, path planning is implemented using bee colony optimization algorithm which is self evolved with certain defined parameters. Artificial bee colony optimization algorithm is approached because of its efficiency, Performance and fewer parameters as compared with existing algorithms. It combines multiple objectives to solve complex strategies and further proves itself to be most prominent algorithm for navigation. Further it is compared with existing algorithms simultaneously.

References
  1. Giovanni M. Bianco,” Getting inspired from Bees to perform large scales visual precise navigation” Proceedings of 2004 IEEEmSJ International Conference on Intelligent Robots and Systems September 28. October 2, 2004. Sendai. Japan, pp: 619-624
  2. Karaboga, Dervis. "An idea based on honey bee swarm for numerical optimization." Technical. Rep. TR06, Erciyes Univ. Press, Erciyes (2005).
  3. D. Karaboga and B. Baştürk, “On the performance of artificial bee colony (ABC) algorithm,” Appl. Soft Computer., vol. 8, no. 1, pp. 687-697, 2008.
  4. D. Karaboga, B. Basturk, “On The Performance Of Artificial Bee Colony (ABC) Algorithm”, Applied Soft Computing, Volume 8, Issue 1, pp. 687-697, January 2008.
  5. Karaboga, D. and Akay, B., “A comparative study of Artificial Bee Colony algorithm,” Applied Mathematics and Computation, In Press, 2009.
  6. D. Karaboga, B. Akay, “A modified artificial bee colony (ABC) algorithm for constrained optimization problems” Applied Soft Computing, Volume 11, Issue 3, pp. 3021–3031, April 2011.
  7. B. Akay, and D. Karaboga, “A Efficient artificial bee colony Algorithm for Real-parameter Optimization, “Information Sciences, Vol. 192, No. 1, pp. 120-142, 2012.
  8. C. Zhang, D. Quyang, and J. Ning, “An Artificial Bee Colony Approach for Clustering,” Expert Systems with Applications, Vol. 37, No. 7, pp. 4761-4767, 2010
  9. F.S.Abu-Mouti and M.E. El-Hawar, “An overview of artificial bee colony algorithm and its applications”, IEEE Transactions on Power Systems, pp. 1-6, 2012.
  10. P.Civicioglu, E. Besdok, "A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms." Artificial Intelligence Review, 39(4): pp. 315-346, 2013.
  11. Preetha Bhattacharjee, “Multi-Robot Path-Planning Using Artificial Bee Colony Optimization Algorithm”, IEEE conference 2011, pp: 219-224.
  12. Nikita, “Self Exploring Approach for path planning in robotic domain”, conference: CSI - 2015; 50th Golden Jubilee Annual Convention,pp:1-6,2015
Index Terms

Computer Science
Information Sciences

Keywords

Path planning artificial bee colony algorithm Particle swarm optimization.