Mobile robot path planning using an improved ant colony optimization

Ant colony algorithm is an intelligent optimization algorithm that is widely used in path planning for mobile robot due to its advantages, such as good feedback information, strong robustness and better distributed computing. However, it has some problems such as the slow convergence and the prematu...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of advanced robotic systems Jg. 15; H. 3
Hauptverfasser: Akka, Khaled, Khaber, Farid
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London, England SAGE Publications 01.05.2018
Sage Publications Ltd
SAGE Publishing
Schlagworte:
Algorithms
Ant colony optimization
Computer networks
Computer simulation
Convergence
Distributed processing
Evaporation rate
Path planning
Robots
Visibility
Ant colony optimization
mobile robot
path planning
grid map
optimal path
ISSN:1729-8806, 1729-8814
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Ant colony algorithm is an intelligent optimization algorithm that is widely used in path planning for mobile robot due to its advantages, such as good feedback information, strong robustness and better distributed computing. However, it has some problems such as the slow convergence and the prematurity. This article introduces an improved ant colony algorithm that uses a stimulating probability to help the ant in its selection of the next grid and employs new heuristic information based on the principle of unlimited step length to expand the vision field and to increase the visibility accuracy; and also the improved algorithm adopts new pheromone updating rule and dynamic adjustment of the evaporation rate to accelerate the convergence speed and to enlarge the search space. Simulation results prove that the proposed algorithm overcomes the shortcomings of the conventional algorithms.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1729-8806
1729-8814
DOI:10.1177/1729881418774673