Comparison between Different Meta-Heuristic Algorithms for Path Planning in Robotics
Author(s) -
Yogita Gigras,
Nikita Jora,
Anuradha Dhull
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016909705
Subject(s) - computer science , meta heuristic , heuristic , robotics , path (computing) , artificial intelligence , motion planning , algorithm , machine learning , robot , programming language
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. General Terms Path planning algorithms
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