Autonomous UAV perching on ledge
Unmanned Aerial Vehicles (UAVs) are playing an ever-increasing role in many fields such as civilian, industrial and military. The development of autonomous technology has made UAVs increasingly intelligent and play an important role in many places where they can replace human power. Despite the many...
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Nanyang Technological University
2022
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sg-ntu-dr.10356-1587002023-07-04T17:48:53Z Autonomous UAV perching on ledge Ye, Han Xie Lihua School of Electrical and Electronic Engineering ELHXIE@ntu.edu.sg Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics Unmanned Aerial Vehicles (UAVs) are playing an ever-increasing role in many fields such as civilian, industrial and military. The development of autonomous technology has made UAVs increasingly intelligent and play an important role in many places where they can replace human power. Despite the many ad- vantages of UAVs, they are often limited by fuel consumption and cannot fly for long periods of time. Based on this situation, we adopt the idea that the UAVs can temporarily land on a roof ledge. By temporarily landing and dock- ing, the UAV can reduce its fuel consumption and increase its usage time and efficiency. This dissertation mainly focuses on the detection part of the perching process, which is the most crucial part of the system. A series of the study was conducted to evaluate the performance of various detection processes such as the multi-plane analysis-based method, the template matching algorithm based on point cloud data, and the deep learning method based on RGB images. The vision-based target detection algorithms can detect potential ledges and thus pro- vide a judgment basis for UAV landing. Practical experiments prove the quality of the approaches. Master of Science (Computer Control and Automation) 2022-05-31T02:52:53Z 2022-05-31T02:52:53Z 2022 Thesis-Master by Coursework Ye, H. (2022). Autonomous UAV perching on ledge. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158700 https://hdl.handle.net/10356/158700 en application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics Ye, Han Autonomous UAV perching on ledge |
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Unmanned Aerial Vehicles (UAVs) are playing an ever-increasing role in many fields such as civilian, industrial and military. The development of autonomous technology has made UAVs increasingly intelligent and play an important role in many places where they can replace human power. Despite the many ad- vantages of UAVs, they are often limited by fuel consumption and cannot fly for long periods of time. Based on this situation, we adopt the idea that the UAVs can temporarily land on a roof ledge. By temporarily landing and dock- ing, the UAV can reduce its fuel consumption and increase its usage time and efficiency. This dissertation mainly focuses on the detection part of the perching process, which is the most crucial part of the system. A series of the study was conducted to evaluate the performance of various detection processes such as the multi-plane analysis-based method, the template matching algorithm based on point cloud data, and the deep learning method based on RGB images. The vision-based target detection algorithms can detect potential ledges and thus pro- vide a judgment basis for UAV landing. Practical experiments prove the quality of the approaches. |
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Xie Lihua |
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Xie Lihua Ye, Han |
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Thesis-Master by Coursework |
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Ye, Han |
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Ye, Han |
title |
Autonomous UAV perching on ledge |
title_short |
Autonomous UAV perching on ledge |
title_full |
Autonomous UAV perching on ledge |
title_fullStr |
Autonomous UAV perching on ledge |
title_full_unstemmed |
Autonomous UAV perching on ledge |
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autonomous uav perching on ledge |
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Nanyang Technological University |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/158700 |
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1772826198157557760 |