A Review: On using ACO Based Hybrid Algorithms for Path Planning of Multi-Mobile Robotics
Dublin Core
Title
A Review: On using ACO Based Hybrid Algorithms for Path Planning of Multi-Mobile Robotics
Subject
Multi-Robotics
path planning (PP)
ACO algorithm
Metaheuristics. uncer-tainties
Description
Abstract-The path planning for Multi Mobile Robotic (MMR) system is a recent combinatorial optimisation problem. In the last decade, many researches have been published to solve this problem. Most of these researches focused on metaheuristic algorithms. This paper reviews articles on Ant Colony Optimisation (ACO) and its hybrid versions to solve the problem. The original Dorigo’s ACO algorithm uses exploration and exploitation phases to find the shortest route in a combinatorial optimisation problem in general without touching mapping, localisation and perception. Due to the properties of MMR, adaptations have been made to ACO algorithms. In this review paper, a literature survey of the recent studies on upgrading, modifications and applications of the ACO algorithms has been discussed to evaluate the application of the different versions of ACO in the MMR domain. The evaluation considered the quality, speed of convergence, robustness, scalability, flexibility of MMR and obstacle avoidance, static and dynamic environment characteristics of the tasks.
Creator
Hamad, Ibrahim Ismael
Hasan, Mohammad S.
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 18 (2020); pp. 145-156
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2020-11-10
Rights
Copyright (c) 2020 Ibrahim Ismael Hamad, Mohammad S. Hasan
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Ibrahim Hamad Ismael and Mohammad Hasan S., A Review: On using ACO Based Hybrid Algorithms for Path Planning of Multi-Mobile Robotics, International Association of Online Engineering (IAOE), Vienna, Austria, 2020, accessed November 7, 2024, https://igi.indrastra.com/items/show/1796