Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)

Path-Planning of a Certain UAV Using Neural-Network Method

Authors
Jie Li, Li Li
Corresponding Author
Jie Li
Available Online November 2016.
DOI
10.2991/aiie-16.2016.44How to use a DOI?
Keywords
Unmanned Aerial Vehicle(UAV), path planning optimization, neural-network
Abstract

Unmanned Aerial Vehicles(UAVs) are widely used for civilian and military purposes, such as surveillance, reconnaissance, search and rescue, border patrol etc. In this paper a single UAV is equipped with a gimballed camera to conduct surveillance operations, the route planning method that uses neural network method is presented. The Neutral network method reduces computational requirements by removing the need for collocation and providing fast computation of gradients and thus the computation costs reduces significantly. The simulation results show the flexibility of the neutral network.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
Series
Advances in Intelligent Systems Research
Publication Date
November 2016
ISBN
978-94-6252-271-8
ISSN
1951-6851
DOI
10.2991/aiie-16.2016.44How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jie Li
AU  - Li Li
PY  - 2016/11
DA  - 2016/11
TI  - Path-Planning of a Certain UAV Using Neural-Network Method
BT  - Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
PB  - Atlantis Press
SP  - 191
EP  - 193
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-16.2016.44
DO  - 10.2991/aiie-16.2016.44
ID  - Li2016/11
ER  -