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Energy efficient path-planning for unmanned aerial vehicle

This project develops an efficient path-planning algorithm for an unmanned aerial vehicle (UAV) in obstacle-rich environments considering minimum energy consumption. UAV is increasingly being used to replace humans in performing risky missions in adverse environments. UAV normally gets its energy fr...

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主要作者:	Debnath, Sanjoy Kumar
格式:	Thesis
语言:	English English English
出版:	2022
主题:	TL Motor vehicles. Aeronautics. Astronautics
在线阅读:	http://eprints.uthm.edu.my/8484/1/24p%20SANJOY%20KUMAR%20DEBNATH.pdf http://eprints.uthm.edu.my/8484/2/SANJOY%20KUMAR%20DEBNATH%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/8484/3/SANJOY%20KUMAR%20DEBNATH%20WATERMARK.pdf http://eprints.uthm.edu.my/8484/
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record_format	eprints
spelling	my.uthm.eprints.84842023-04-02T00:52:13Z http://eprints.uthm.edu.my/8484/ Energy efficient path-planning for unmanned aerial vehicle Debnath, Sanjoy Kumar TL Motor vehicles. Aeronautics. Astronautics This project develops an efficient path-planning algorithm for an unmanned aerial vehicle (UAV) in obstacle-rich environments considering minimum energy consumption. UAV is increasingly being used to replace humans in performing risky missions in adverse environments. UAV normally gets its energy from solar, hydrogen cell or li-ion batteries. However, these energy sources have limitations; for example, in a cloudy day, solar power might not be fully generated. This may result in the UAV to fail in accomplishing a given mission if its path is longer than necessary. Therefore, it is vital for the UAV to have a minimal path length which leads to the least energy consumption. The proposed path planning algorithm is called Iterative Elliptical- Convex Visibility Graph (IECoVG) which is based on visibility graph (VG) and Dijkstra’s algorithm. IECoVG limits the size of the search space which will in turn reduce the number of obstacles for path planning. Performance comparison through simulation in terms of computational time and path length between IECoVG andconventional VG as well as the Iterative Equilateral Space Oriented VG (IESOVG)has been executed. Identical scenarios have been applied in order to have a fair and conclusive result. The simulation shows that IECoVG improves the computation time up to 86 % due to its efficiency in selecting the search space. To further enhance IECoVG, flight cost, segment length, heading angle change and the UAV’s speed have also been considered as they proportionally affect the energy consumption of the UAV. The enhanced IECoVG named IECoVG+ can improve the energy consumption of the UAV by 10.42 %. 2022-04 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/8484/1/24p%20SANJOY%20KUMAR%20DEBNATH.pdf text en http://eprints.uthm.edu.my/8484/2/SANJOY%20KUMAR%20DEBNATH%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/8484/3/SANJOY%20KUMAR%20DEBNATH%20WATERMARK.pdf Debnath, Sanjoy Kumar (2022) Energy efficient path-planning for unmanned aerial vehicle. Doctoral thesis, Universiti Tun Hussein Onn Malaysia.
institution	Universiti Tun Hussein Onn Malaysia
building	UTHM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tun Hussein Onn Malaysia
content_source	UTHM Institutional Repository
url_provider	http://eprints.uthm.edu.my/
language	English English English
topic	TL Motor vehicles. Aeronautics. Astronautics
spellingShingle	TL Motor vehicles. Aeronautics. Astronautics Debnath, Sanjoy Kumar Energy efficient path-planning for unmanned aerial vehicle
description	This project develops an efficient path-planning algorithm for an unmanned aerial vehicle (UAV) in obstacle-rich environments considering minimum energy consumption. UAV is increasingly being used to replace humans in performing risky missions in adverse environments. UAV normally gets its energy from solar, hydrogen cell or li-ion batteries. However, these energy sources have limitations; for example, in a cloudy day, solar power might not be fully generated. This may result in the UAV to fail in accomplishing a given mission if its path is longer than necessary. Therefore, it is vital for the UAV to have a minimal path length which leads to the least energy consumption. The proposed path planning algorithm is called Iterative Elliptical- Convex Visibility Graph (IECoVG) which is based on visibility graph (VG) and Dijkstra’s algorithm. IECoVG limits the size of the search space which will in turn reduce the number of obstacles for path planning. Performance comparison through simulation in terms of computational time and path length between IECoVG andconventional VG as well as the Iterative Equilateral Space Oriented VG (IESOVG)has been executed. Identical scenarios have been applied in order to have a fair and conclusive result. The simulation shows that IECoVG improves the computation time up to 86 % due to its efficiency in selecting the search space. To further enhance IECoVG, flight cost, segment length, heading angle change and the UAV’s speed have also been considered as they proportionally affect the energy consumption of the UAV. The enhanced IECoVG named IECoVG+ can improve the energy consumption of the UAV by 10.42 %.
format	Thesis
author	Debnath, Sanjoy Kumar
author_facet	Debnath, Sanjoy Kumar
author_sort	Debnath, Sanjoy Kumar
title	Energy efficient path-planning for unmanned aerial vehicle
title_short	Energy efficient path-planning for unmanned aerial vehicle
title_full	Energy efficient path-planning for unmanned aerial vehicle
title_fullStr	Energy efficient path-planning for unmanned aerial vehicle
title_full_unstemmed	Energy efficient path-planning for unmanned aerial vehicle
title_sort	energy efficient path-planning for unmanned aerial vehicle
publishDate	2022
url	http://eprints.uthm.edu.my/8484/1/24p%20SANJOY%20KUMAR%20DEBNATH.pdf http://eprints.uthm.edu.my/8484/2/SANJOY%20KUMAR%20DEBNATH%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/8484/3/SANJOY%20KUMAR%20DEBNATH%20WATERMARK.pdf http://eprints.uthm.edu.my/8484/
_version_	1762394683774861312
score	13.250246

Energy efficient path-planning for unmanned aerial vehicle

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