Simulation and experimental approach for optimal path planning of UAV using A* and MEA* algorithms

Over the past decades, Unmanned Aerial Vehicle (UAV) have been effectively adapted to perform disaster missions, agricultural and various societal applications. The path planning plays a crucial role in bringing autonomy to the UAVs to attain the designated tasks by avoiding collision in the obstacl...

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Autores principales:	Esakki Balasubramanian, Marreddy Gayatri, Ganesh M. Sai, Elangovan E.
Formato:	article
Lenguaje:	EN
Publicado:	EDP Sciences 2021
Materias:	optimal path planning a* algorithm mea* algorithm simulation obstacle avoidance unmanned aerial vehicle Industrial engineering. Management engineering T55.4-60.8 Industrial directories T11.95-12.5
Acceso en línea:	https://doaj.org/article/23e22993e8ab4b809c83b6661ce561a7
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id	oai:doaj.org-article:23e22993e8ab4b809c83b6661ce561a7
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spelling	oai:doaj.org-article:23e22993e8ab4b809c83b6661ce561a72021-11-08T15:22:38ZSimulation and experimental approach for optimal path planning of UAV using A* and MEA* algorithms1779-628810.1051/smdo/2021024https://doaj.org/article/23e22993e8ab4b809c83b6661ce561a72021-01-01T00:00:00Zhttps://www.ijsmdo.org/articles/smdo/full_html/2021/01/smdo210077/smdo210077.htmlhttps://doaj.org/toc/1779-6288Over the past decades, Unmanned Aerial Vehicle (UAV) have been effectively adapted to perform disaster missions, agricultural and various societal applications. The path planning plays a crucial role in bringing autonomy to the UAVs to attain the designated tasks by avoiding collision in the obstacles prone regions. Optimal path planning of UAV is considered to be a challenging issue in real time navigation during obstacle prone environments. The present article focused on implementing a well-known A* and variant of A* namely MEA* algorithm to determine an optimal path in the varied obstacle regions for the UAV applications which is novel. Simulation is performed to investigate the performance of each algorithm with respect to comparing their execution time, total distance travelled and number of turns made to reach the source to target. Further, experimental flight trails are made to examine the performance of these algorithms using a UAV. The desired position, velocity and yaw of UAV is obtained based on the waypoints of optimal path planned data and effective navigation is performed. The simulation and experimental results are compared for confirming the effectiveness of these algorithms.Esakki BalasubramanianMarreddy GayatriGanesh M. SaiElangovan E.EDP Sciencesarticleoptimal path planninga* algorithmmea* algorithmsimulationobstacle avoidanceunmanned aerial vehicleIndustrial engineering. Management engineeringT55.4-60.8Industrial directoriesT11.95-12.5ENInternational Journal for Simulation and Multidisciplinary Design Optimization, Vol 12, p 24 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	optimal path planning a* algorithm mea* algorithm simulation obstacle avoidance unmanned aerial vehicle Industrial engineering. Management engineering T55.4-60.8 Industrial directories T11.95-12.5
spellingShingle	optimal path planning a* algorithm mea* algorithm simulation obstacle avoidance unmanned aerial vehicle Industrial engineering. Management engineering T55.4-60.8 Industrial directories T11.95-12.5 Esakki Balasubramanian Marreddy Gayatri Ganesh M. Sai Elangovan E. Simulation and experimental approach for optimal path planning of UAV using A* and MEA* algorithms
description	Over the past decades, Unmanned Aerial Vehicle (UAV) have been effectively adapted to perform disaster missions, agricultural and various societal applications. The path planning plays a crucial role in bringing autonomy to the UAVs to attain the designated tasks by avoiding collision in the obstacles prone regions. Optimal path planning of UAV is considered to be a challenging issue in real time navigation during obstacle prone environments. The present article focused on implementing a well-known A* and variant of A* namely MEA* algorithm to determine an optimal path in the varied obstacle regions for the UAV applications which is novel. Simulation is performed to investigate the performance of each algorithm with respect to comparing their execution time, total distance travelled and number of turns made to reach the source to target. Further, experimental flight trails are made to examine the performance of these algorithms using a UAV. The desired position, velocity and yaw of UAV is obtained based on the waypoints of optimal path planned data and effective navigation is performed. The simulation and experimental results are compared for confirming the effectiveness of these algorithms.
format	article
author	Esakki Balasubramanian Marreddy Gayatri Ganesh M. Sai Elangovan E.
author_facet	Esakki Balasubramanian Marreddy Gayatri Ganesh M. Sai Elangovan E.
author_sort	Esakki Balasubramanian
title	Simulation and experimental approach for optimal path planning of UAV using A* and MEA* algorithms
title_short	Simulation and experimental approach for optimal path planning of UAV using A* and MEA* algorithms
title_full	Simulation and experimental approach for optimal path planning of UAV using A* and MEA* algorithms
title_fullStr	Simulation and experimental approach for optimal path planning of UAV using A* and MEA* algorithms
title_full_unstemmed	Simulation and experimental approach for optimal path planning of UAV using A* and MEA* algorithms
title_sort	simulation and experimental approach for optimal path planning of uav using a* and mea* algorithms
publisher	EDP Sciences
publishDate	2021
url	https://doaj.org/article/23e22993e8ab4b809c83b6661ce561a7
work_keys_str_mv	AT esakkibalasubramanian simulationandexperimentalapproachforoptimalpathplanningofuavusingaandmeaalgorithms AT marreddygayatri simulationandexperimentalapproachforoptimalpathplanningofuavusingaandmeaalgorithms AT ganeshmsai simulationandexperimentalapproachforoptimalpathplanningofuavusingaandmeaalgorithms AT elangovane simulationandexperimentalapproachforoptimalpathplanningofuavusingaandmeaalgorithms
_version_	1718441732158259200

Simulation and experimental approach for optimal path planning of UAV using A* and MEA* algorithms

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