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

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