CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Metaheuristic Algorithm for Robotic Path Planning

by Yogita Gigras, Kusum Gupta
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 85 - Number 3
Year of Publication: 2014
Authors: Yogita Gigras, Kusum Gupta
10.5120/14822-3056

Yogita Gigras, Kusum Gupta . Metaheuristic Algorithm for Robotic Path Planning. International Journal of Computer Applications. 85, 3 ( January 2014), 26-29. DOI=10.5120/14822-3056

@article{ 10.5120/14822-3056,
author = { Yogita Gigras, Kusum Gupta },
title = { Metaheuristic Algorithm for Robotic Path Planning },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 85 },
number = { 3 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 26-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume85/number3/14822-3056/ },
doi = { 10.5120/14822-3056 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:01:32.760395+05:30
%A Yogita Gigras
%A Kusum Gupta
%T Metaheuristic Algorithm for Robotic Path Planning
%J International Journal of Computer Applications
%@ 0975-8887
%V 85
%N 3
%P 26-29
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a metaheuristic optimization algorithm for mobile robot path planning problem. A comparative study between particle swarm and ant colony optimization algorithm is conducted. The experimental study shows that the ant colony optimization algorithm outperforms over particle swarm optimization in terms of computational time.

References
  1. Beatriz A. Garro, Humberto Sossa and Roberto A. Vázquez. 2006, "Path Planning Optimization Using Bio-Inspirited Algorithms", International Conference on Artificial Intelligence, 319 – 330.
  2. Abdullah Zawawi Mohamed, Sang Heon Lee , Mahfuz Aziz, Hung Yao Hsu,Wahid Md Ferdous. 2010"A Proposal on Development of Intelligent PSO Based Path Planning and Image Based Obstacle Avoidance for Real Multi Agents Robotics System Application", International Conference on Electronic Computer Technology (ICECT), 128 – 132.
  3. X. -S. Yang. 2009,"Harmony Search as a Metaheuristic Algorithm", in: Music-Inspired Harmony Search Algorithm: Theory and Applications (EditorZ. W. Geem), Studies in Computational Intelligence, Springer Berlin, Vol. 191, 1-14.
  4. M. Sabry Hassouna, Alaa E. Abdel-Hakim, and A. A. Farag. 2005 "Robust Robotic Path Planning Using Level Sets", IEEE International Conference on Image Processing, Vol. 3, pp. III - 473-6.
  5. Chia-Feng Juang, Senior Member, IEEE, and Chun-Ming Lu. 2009, "Ant Colony Optimization Incorporated With Fuzzy Q-Learning for Reinforcement Fuzzy Control", IEEE Transactions on Systems, Man, and Cybernetics —Part A: Systems and Humans, Vol. 39, No. 3.
  6. Alireza rezaee, Mohammad jafar pour jalali. 2009 "Multi-Resolution Ant Colony A New Approach to Use Swarm Intelligence in Continuous Problems", International Conference on Information and Multimedia Technology, pp: 529 – 532.
  7. Gireesh Kumar . T, Vinodh. P. Vijayan . 2007. "A Multi-agent Optimal Path Planning Approach to Robotics Environment", International Conference on Computational Intelligence and Multimedia Applications, Vol. 1, pp. 400 – 404.
Index Terms

Computer Science
Information Sciences

Keywords

Path planning Ant colony optimization algorithm (ACO) and Particle swarm optimization (PSO).

Powered by PhDFocusTM