Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/414324
Title: Vision based autonomous navigation of unmanned aerial vehicle uav for wireless power charging
Researcher: Anumula swarnalatha
Guide(s): Anitha, G
Keywords: Engineering and Technology
Engineering
Engineering Electrical and Electronic
autonomous navigation
aerial vehicle
University: Anna University
Completed Date: 2022
Abstract: Unmanned aerial vehicles (UAV)/Quadcopters are widely used in defence, agriculture, medicine, and various other fields for surveillance and reconnaissance purposes. Even though Quadcopters are quite useful, battery power restrictions limit the prolonged flight duration, and they require battery recharge quite frequently. To overcome these shortcomings, autonomous charging of the Quadcopter is essential for an uninterrupted flight. Some researchers have proposed contact-based charging points for autonomous recharging for a drone. But the problem of this technique is that the perfect alignment of the electrodes to the charging point is required for the recharging of the UAV battery which inturn needs human intervention. Wireless charging of Quadcopters is thus a desired and efficient method to address this challenge. Hence this research explores the concept of wireless charging of a Quad copter s battery using vision-based navigation to enable continuous surveillance. For getting the battery charged wirelessly, Quadcopter has to navigate to a charging-pad using Global position navigation system (GPS) coordinates. However, precise landing may not be achieved due to inaccuracy in GPS method of landing. Vision-based guidance addresses this challenge by providing more accurate information about the charging pad s position, helping the vehicle move towards the charging-pad and get charged wirelessly. The endurance can be enhanced by providing many charging points around the surveillance area. The main objectives of this thesis are: To identify the nearest charging pad using Haversine distance function such that Quadcopter can reach the nearest charging pad quickly.To develop a vision-based centroid detection algorithm in an image processing computer (Raspberry pi B+) to detect the charging pad and move Quadcopter towards charging pad autonomously. To design and development of wireless power charging by using inductive coupling to recharge the battery of Quadcopter. To implement super capacitors in the charging circuit in order to make the charging cycle efficient. newline newline newline newline
Pagination: p.106-117
URI: http://hdl.handle.net/10603/414324
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File25.42 kBAdobe PDFView/Open
02_prelim pages.pdf1.98 MBAdobe PDFView/Open
03_contents.pdf13.13 kBAdobe PDFView/Open
04_abstracts.pdf141.92 kBAdobe PDFView/Open
05_chapter 1.pdf619.72 kBAdobe PDFView/Open
06_chapter 2.pdf1.49 MBAdobe PDFView/Open
07_chapter 3.pdf1.25 MBAdobe PDFView/Open
08_chapter 4.pdf1.73 MBAdobe PDFView/Open
09_chapter 5.pdf1.45 MBAdobe PDFView/Open
10_annexures.pdf143.29 kBAdobe PDFView/Open
80_recommendation.pdf86.15 kBAdobe PDFView/Open
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