Flight path planning using GA and fuzzy logic considering communication constraints

Kermani, Pedram; Afzalian, Ali A.

doi:10.1109/istel.2014.7000661

Cited by 7 publications

(6 citation statements)

References 8 publications

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“…The dimension of the environment is 18, 000 by 45, 000, with the accuracy of 90 square meters. As presented in [14] the fuzzy map is a matrix of 200 by 500. Each point in the matrix presenteda definite performance functions according to the three specified constraints.…”

Section: The Results Of Simulationmentioning

confidence: 99%

“…The proposed method was compared with the two methods of PSO [8] and GA [14]. For this reason all the three methods were run a hundred times in different environments and with different sources and destinations.…”

Section: A Comparison With Other Methodsmentioning

confidence: 99%

“…To implement the GA, similar specified settings in reference [14] was applied. It is noteworthy here in GA method, after completion of the minimum routing, the path was badly broken and comprised broken parts which can be softened by the softener specified in reference [14].…”

Section: A Comparison With Other Methodsmentioning

confidence: 99%

“…The modeling of [14] is adopted in this article in which the aforementioned three constraints have been modeled with the phase machine. The presented model specifies the performance function of the problem.…”

Section: Definition Of the Problem And The Evaluation Functionmentioning

confidence: 99%

“…Two recently proposed methods, which we will compare our method with those, are the particle swarm optimization (PSO) is used in [8], and theGA [14]. This comparison is on the basis of the calculation time and better direction in regard to fuzzy map.…”

Section: Definition Of the Problem And The Evaluation Functionmentioning

confidence: 99%

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Offine/online Optimum Routing of a UAV using Auxiliary Points

Fadavi

Beheshti

Kermani

2017

IJECE

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This paper presents a method to determine the route of a three-dimensional UAV. Three criteria; the height, the length of flight path and the un authorized areas are used as the constraints and combined in a fuzzy function as the evaluation function. The article aimed to discover a minimum cost route from source to destination considering the constrains. In this paper a new searching methodis proposed, with use of auxiliary points. The auxiliary point method iterativelydivides a straight line to two shorter lines with less cost of evaluation function. Implementation results show that the proposed method dramatically decreasesthe calculations; meanwhile the ight route is sub-optimum. Keyword:Evaluation Fuzzy systems Three-dimensional routing UAV Copyright © 2017 Institute of Advanced Engineering and Science.All rights reserved. Corresponding Author:Abbas Fadavi, Department of Mechatronics, Science and Research Branch, Islamic Azad Univercity, Semnan, Iran Email: abbas_fadavi@yahoo.com INTRODUCTIONUVA has its application mainly in the military industry [1][2][3]. However, it is used in a large number of non-civilian applications, such as fire fighting, meteorology, aerial photography and research projects. The aim of this article is to discover an appropriate route for the UAVs. An optimum route is a minimum distance route one which best satisfies the constraints. Different methods have been introduced and discussed in order to determine the optimal auxiliarypoints. Various articles have been presented to determine the optimal route forthe UVAs. A number of these articles have made use of classic methods. [11] applied hierarchical decision making. Their, the intended environment was first examined and divided into different areas. Then, according to the rate of the constraints satisfaction problems, the best identification areas and the paths were specified inorder to be able to reach the destination from the source among optimum zonesand to discover the best path. The method of Dijkstra was used. Robergeetal [12] presented a definite cost function. This function utilized a combination of different constraints like distance length with dangerous points and the rate of fuel consumption. Then, the optimal path was calculated using genetic algorithms or PSO based on minimizing or maximizing the cost function. Also, researchers like Kok et al [13] applied executive points to their hardware routing implementation. In article [11] the environment was first examined and divided into different zones. Then, optimal zones were identified. These are the zones which better satisfied the points inside the zones of

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Section: The Results Of Simulationmentioning

confidence: 99%

Section: A Comparison With Other Methodsmentioning

confidence: 99%

Section: A Comparison With Other Methodsmentioning

confidence: 99%

Section: Definition Of the Problem And The Evaluation Functionmentioning

confidence: 99%

Section: Definition Of the Problem And The Evaluation Functionmentioning

confidence: 99%

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Offine/online Optimum Routing of a UAV using Auxiliary Points

Fadavi

Beheshti

Kermani

2017

IJECE

Self Cite

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Flight Path Planning of Aircraft Under Multiple Constraints Based on Genetic Algorithm

Guo

Liu

Abdullah

2023

Lecture Notes on Data Engineering and Communications Technologies

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UAV path planning techniques: a survey

Ghambari,

Golabi,

Jourdan

et al. 2024

RAIRO-Oper. Res.

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Unmanned Aerial Vehicles (UAVs) are ideally suited for many real-world applications ranging from scientific to commercial, industrial, and military fields. Enhancing the efficiency of UAV-based missions through optimization techniques is of paramount significance. Unmanned Aerial Vehicles (UAVs) are ideally suited for many real-world applications ranging from scientific to commercial, industrial, and military fields. Enhancing the efficiency of UAV-based missions through optimization techniques is of paramount significance. In this regard, the path planning problem that refers to finding the best collision-free path between the start point and the destination by addressing temporal, physical, and geometric constraints is a key issue. In this paper, a review of recent path planning methods from different perspectives with a clear and comprehensive categorization is presented. This study provides a general taxonomy categorizing the existing works into classical approaches, soft-computing techniques, and hybrid methods. Here, a detailed analysis of the recent techniques as well as their advantages and limitations is offered. Additionally, it provides an overview of environment modeling methods, path structures, optimality criteria, completeness criteria, and current UAV simulators.

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Flight path planning using GA and fuzzy logic considering communication constraints

Cited by 7 publications

References 8 publications

Offine/online Optimum Routing of a UAV using Auxiliary Points

Offine/online Optimum Routing of a UAV using Auxiliary Points

Flight Path Planning of Aircraft Under Multiple Constraints Based on Genetic Algorithm

UAV path planning techniques: a survey

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