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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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Bibliographic Details
Main Author: Debnath, Sanjoy Kumar
Format: Thesis
Language:English
English
English
Published: 2022
Subjects:
TL Motor vehicles. Aeronautics. Astronautics
Online Access: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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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 13.250893

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