國立虎尾科技大學 |

Deployment of Real Time UAV Aerial Surveillance with Coverage Strength Model.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Deployment of Real Time UAV Aerial Surveillance with Coverage Strength Model./
作者:	Zhang, Tong.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	78 p.
附註:	Source: Masters Abstracts International, Volume: 57-02.
Contained By:	Masters Abstracts International57-02(E).
標題:	Robotics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10640200
ISBN:	9780355491203

Deployment of Real Time UAV Aerial Surveillance with Coverage Strength Model.
Zhang, Tong.

Deployment of Real Time UAV Aerial Surveillance with Coverage Strength Model. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 78 p.

Source: Masters Abstracts International, Volume: 57-02.

Thesis (M.A.Sc.)--University of Windsor (Canada), 2017.

This thesis assesses the feasibility of applying coverage model to the problem of using unmanned aerial vehicles (UAVs) for aerial surveillances. The purpose of aerial surveillance is using sensors to cover the task area to obtain the information regarding to this area, such as environmental study. Comparing to static sensors, business purposes UAVs have higher mobility. Since static sensors have limited sensing range, it is not possible to use them to cover the task area. UAVs with sensors onboard can be used for surveillance and save the data to obtain more detailed information of the task area. The data retrieved by the sensors can be used for developing autonomous control algorithms for navigation of the UAV. However, there are some inevitable factors that shortens the flight time of the UAV. For example, considering the maximum payload of the UAV, the battery of UAV can usually last at most 30 minutes since it cannot be very large. It is very important to improve the efficiency of UAV surveillance by pre-designing the flight path for one UAVs or deployment positions for multiple UAVs.

ISBN: 9780355491203Subjects--Topical Terms:

561941
Robotics.

Deployment of Real Time UAV Aerial Surveillance with Coverage Strength Model.
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300 $a 78 p.
500 $a Source: Masters Abstracts International, Volume: 57-02.
500 $a Adviser: Xiang Chen.
502 $a Thesis (M.A.Sc.)--University of Windsor (Canada), 2017.
520 $a This thesis assesses the feasibility of applying coverage model to the problem of using unmanned aerial vehicles (UAVs) for aerial surveillances. The purpose of aerial surveillance is using sensors to cover the task area to obtain the information regarding to this area, such as environmental study. Comparing to static sensors, business purposes UAVs have higher mobility. Since static sensors have limited sensing range, it is not possible to use them to cover the task area. UAVs with sensors onboard can be used for surveillance and save the data to obtain more detailed information of the task area. The data retrieved by the sensors can be used for developing autonomous control algorithms for navigation of the UAV. However, there are some inevitable factors that shortens the flight time of the UAV. For example, considering the maximum payload of the UAV, the battery of UAV can usually last at most 30 minutes since it cannot be very large. It is very important to improve the efficiency of UAV surveillance by pre-designing the flight path for one UAVs or deployment positions for multiple UAVs.
520 $a The coverage strength model converts parameter of sensors into geometrical constraints, which allows using mathematical equations to represent the sensor and using convex optimization to find deployment of multiple sensors to cover the task area with best visual coverage and image quality. The coverage model consists of three different models: sensor model, environmental model, and task model. The convex function is constructed based on the three models and optimized to the minimum to get the best deployment.
520 $a It is also possible to use autonomous UAV in this application. Thus, the controlling algorithm is also a part of this thesis. Different from application of indoor UAVs, only GPS can be used for positioning and navigating the movement of the UAV. A black box control only based on GPS is presented.
520 $a The contributions of this thesis are in two perspectives. First, it applies the coverage strength model to mobile sensors, UAVs. It improves the efficiency of using UAVs to survey the task area. With the method applied, it may need less hardware requirements and time to achieve good result. Second, it is an autonomous UAV that is built for this application. Therefore, every detail of building this drone is introduced in this application including all hardware and software details.
520 $a In the following parts of the thesis, the coverage strength model is introduced. The instruments and the controlling algorithm of the UAV are presented. The experimental procedure and the result of applying the coverage strength model are shown as well.
590 $a School code: 0115.
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