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Reseach Article

Adaptive Path Selection using Meta-heuristic Ping Method

by Simarpreet Kaur, Amit Grover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 145 - Number 6
Year of Publication: 2016
Authors: Simarpreet Kaur, Amit Grover
10.5120/ijca2016910527

Simarpreet Kaur, Amit Grover . Adaptive Path Selection using Meta-heuristic Ping Method. International Journal of Computer Applications. 145, 6 ( Jul 2016), 1-4. DOI=10.5120/ijca2016910527

@article{ 10.5120/ijca2016910527,
author = { Simarpreet Kaur, Amit Grover },
title = { Adaptive Path Selection using Meta-heuristic Ping Method },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 145 },
number = { 6 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume145/number6/25279-2016910527/ },
doi = { 10.5120/ijca2016910527 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:48:01.459462+05:30
%A Simarpreet Kaur
%A Amit Grover
%T Adaptive Path Selection using Meta-heuristic Ping Method
%J International Journal of Computer Applications
%@ 0975-8887
%V 145
%N 6
%P 1-4
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The unmanned aerial vehicles (UAV) can be used in various fields such as weather applications, military applications, remote sensing, oceanography etc. There are many problems for UAV to find best and obstacle free path by detecting obstacle and calculate turn. In this paper, a novel method has proposed model for the obstacle free UAV routing by using the multi-factor distances. The proposed model is entirely based upon the UAV turn calculation based shortest path with minimum number of obstacles and turns. The multi-factor distance has been computed which includes the distance between the source and destination, UAV and obstacles, obstacles and obstacles, angle of rotation (Degree of rotation) and other several factors. This proposed model is also sufficient to track the fuel and find best have been obtained in the form of various network parameters of latency of the hurdle detection. energy consumption, load, route persistence comparison. The experimental results have advocated the robustness of the path planning solution for the UAV path planning.

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Index Terms

Computer Science
Information Sciences

Keywords

UAV Routing collision avoidance alternative path planning collision detection