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An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning
Joint Authors
Appiah, Albert Yaw
Ayawli, Ben Beklisi Kwame
Kyeremeh, Frimpong
Chellali, Ryad
Source
Journal of Advanced Transportation
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-27, 27 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-07-19
Country of Publication
Egypt
No. of Pages
27
Main Subjects
Abstract EN
Safe and smooth mobile robot navigation through cluttered environment from the initial position to goal with optimal path is required to achieve intelligent autonomous ground vehicles.
There are countless research contributions from researchers aiming at finding solution to autonomous mobile robot path planning problems.
This paper presents an overview of nature-inspired, conventional, and hybrid path planning strategies employed by researchers over the years for mobile robot path planning problem.
The main strengths and challenges of path planning methods employed by researchers were identified and discussed.
Future directions for path planning research is given.
The results of this paper can significantly enhance how effective path planning methods could be employed and implemented to achieve real-time intelligent autonomous ground vehicles.
American Psychological Association (APA)
Ayawli, Ben Beklisi Kwame& Chellali, Ryad& Appiah, Albert Yaw& Kyeremeh, Frimpong. 2018. An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-27.
https://search.emarefa.net/detail/BIM-1181724
Modern Language Association (MLA)
Ayawli, Ben Beklisi Kwame…[et al.]. An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning. Journal of Advanced Transportation No. 2018 (2018), pp.1-27.
https://search.emarefa.net/detail/BIM-1181724
American Medical Association (AMA)
Ayawli, Ben Beklisi Kwame& Chellali, Ryad& Appiah, Albert Yaw& Kyeremeh, Frimpong. An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-27.
https://search.emarefa.net/detail/BIM-1181724
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181724