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Multi-drones energy efficient based path planning optimization using Genetic Algorithm and Gradient Decent approach

The paper introduces an efficient energy optimization technique for multi-drones through path planning using Genetic Algorithm (GA) and Gradient Descent (GD). This approach minimizes energy consumption and avoids obstacles by optimizing path-planning decisions based on real-time drone velocity and o...

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Main Authors:	Mustafa, Yousra A, Ali, Elmustafa S, Osman, Thana E, Khalifa, Othman Omran, Mohamed, Zainb O, Saeed, Rashid A, Saeed, Mamoon M
Format:	Proceeding Paper
Language:	English English
Published:	IEEE 2024
Subjects:	T Technology (General) T10.5 Communication of technical information TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/114448/1/114448_Multi-drones%20energy%20efficient%20based.pdf http://irep.iium.edu.my/114448/7/114448_Multi-drones%20energy%20efficient%20based_SCOPUS.pdf http://irep.iium.edu.my/114448/ https://ieeexplore.ieee.org/document/10652441
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spelling	my.iium.irep.1144482024-09-25T02:40:46Z http://irep.iium.edu.my/114448/ Multi-drones energy efficient based path planning optimization using Genetic Algorithm and Gradient Decent approach Mustafa, Yousra A Ali, Elmustafa S Osman, Thana E Khalifa, Othman Omran Mohamed, Zainb O Saeed, Rashid A Saeed, Mamoon M T Technology (General) T10.5 Communication of technical information TK Electrical engineering. Electronics Nuclear engineering The paper introduces an efficient energy optimization technique for multi-drones through path planning using Genetic Algorithm (GA) and Gradient Descent (GD). This approach minimizes energy consumption and avoids obstacles by optimizing path-planning decisions based on real-time drone velocity and obstacle proximity. GD complements GA by refining path fitness through distance measurements, allowing drones to dynamically adjust their routes amid environmental and energy constraints. Experimental results demonstrate that the hybrid GA/GD approach significantly reduces energy usage while maintaining safe navigation and optimizing path costs. Compared to GA alone, the hybrid method achieves a remarkable 22.62% average reduction in energy consumption, highlighting its superior performance in energy-efficient multi-drone path planning. IEEE 2024-09-04 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/114448/1/114448_Multi-drones%20energy%20efficient%20based.pdf application/pdf en http://irep.iium.edu.my/114448/7/114448_Multi-drones%20energy%20efficient%20based_SCOPUS.pdf Mustafa, Yousra A and Ali, Elmustafa S and Osman, Thana E and Khalifa, Othman Omran and Mohamed, Zainb O and Saeed, Rashid A and Saeed, Mamoon M (2024) Multi-drones energy efficient based path planning optimization using Genetic Algorithm and Gradient Decent approach. In: 9th International Conference on Mechatronics Engineering (ICOM 2024), 13th - 14th August 2024, Kuala Lumpur, Malaysia. https://ieeexplore.ieee.org/document/10652441 10.1109/ICOM61675.2024.10652441
institution	Universiti Islam Antarabangsa Malaysia
building	IIUM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	International Islamic University Malaysia
content_source	IIUM Repository (IREP)
url_provider	http://irep.iium.edu.my/
language	English English
topic	T Technology (General) T10.5 Communication of technical information TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	T Technology (General) T10.5 Communication of technical information TK Electrical engineering. Electronics Nuclear engineering Mustafa, Yousra A Ali, Elmustafa S Osman, Thana E Khalifa, Othman Omran Mohamed, Zainb O Saeed, Rashid A Saeed, Mamoon M Multi-drones energy efficient based path planning optimization using Genetic Algorithm and Gradient Decent approach
description	The paper introduces an efficient energy optimization technique for multi-drones through path planning using Genetic Algorithm (GA) and Gradient Descent (GD). This approach minimizes energy consumption and avoids obstacles by optimizing path-planning decisions based on real-time drone velocity and obstacle proximity. GD complements GA by refining path fitness through distance measurements, allowing drones to dynamically adjust their routes amid environmental and energy constraints. Experimental results demonstrate that the hybrid GA/GD approach significantly reduces energy usage while maintaining safe navigation and optimizing path costs. Compared to GA alone, the hybrid method achieves a remarkable 22.62% average reduction in energy consumption, highlighting its superior performance in energy-efficient multi-drone path planning.
format	Proceeding Paper
author	Mustafa, Yousra A Ali, Elmustafa S Osman, Thana E Khalifa, Othman Omran Mohamed, Zainb O Saeed, Rashid A Saeed, Mamoon M
author_facet	Mustafa, Yousra A Ali, Elmustafa S Osman, Thana E Khalifa, Othman Omran Mohamed, Zainb O Saeed, Rashid A Saeed, Mamoon M
author_sort	Mustafa, Yousra A
title	Multi-drones energy efficient based path planning optimization using Genetic Algorithm and Gradient Decent approach
title_short	Multi-drones energy efficient based path planning optimization using Genetic Algorithm and Gradient Decent approach
title_full	Multi-drones energy efficient based path planning optimization using Genetic Algorithm and Gradient Decent approach
title_fullStr	Multi-drones energy efficient based path planning optimization using Genetic Algorithm and Gradient Decent approach
title_full_unstemmed	Multi-drones energy efficient based path planning optimization using Genetic Algorithm and Gradient Decent approach
title_sort	multi-drones energy efficient based path planning optimization using genetic algorithm and gradient decent approach
publisher	IEEE
publishDate	2024
url	http://irep.iium.edu.my/114448/1/114448_Multi-drones%20energy%20efficient%20based.pdf http://irep.iium.edu.my/114448/7/114448_Multi-drones%20energy%20efficient%20based_SCOPUS.pdf http://irep.iium.edu.my/114448/ https://ieeexplore.ieee.org/document/10652441
_version_	1811679641367216128
score	13.211869

Multi-drones energy efficient based path planning optimization using Genetic Algorithm and Gradient Decent approach

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