Tracking and precise landing by a quadrotor
For a drone to land precisely on a target in a flat terrain, it must accurately estimate its 4-dimensional (4D) position, which are the x-y-z coordinates and yaw orientation, with respect to its landing target. In this Final Year Project (FYP), we seek to investigate, adapt, and apply 4D pose estima...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/158054 |
| _version_ | 1826120773214928896 |
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| author | Hoo, Shi Jan |
| author2 | Ling Keck Voon |
| author_facet | Ling Keck Voon Hoo, Shi Jan |
| author_sort | Hoo, Shi Jan |
| collection | NTU |
| description | For a drone to land precisely on a target in a flat terrain, it must accurately estimate its 4-dimensional (4D) position, which are the x-y-z coordinates and yaw orientation, with respect to its landing target. In this Final Year Project (FYP), we seek to investigate, adapt, and apply 4D pose estimation research for the purpose of drone landing on a ground robot in a flat terrain. A quadrotor and ground robot are simulated in a robot software environment in which the devised methodologies are implemented on the simulated drone to estimate its 4D pose with respect to the ground robot. The accuracy of the proposed implementation is measured by comparing the generated 4D pose estimates with the actual 4D pose values provided by the simulation. In an overview, the main methods used are deep learning for image points prediction, an efficient solution for the Perspective-N-Point (PNP) problem, and the Kalman filter for filtering / smoothening noisy estimates. These methods will be combined in tandem to form a pipeline for continuous pose estimation for the drone. In addition to this constructed pipeline, a section has been dedicated to exploratively address the problem of occlusion using Generative Adversarial Network, or in short GAN. Overall, the success of methods implemented within the simulation allows us to construct a proof-of-concept for 4D pose estimation on a real-life drone. |
| first_indexed | 2024-10-01T05:21:55Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/158054 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:21:55Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1580542023-07-07T19:21:35Z Tracking and precise landing by a quadrotor Hoo, Shi Jan Ling Keck Voon School of Electrical and Electronic Engineering Institute of Infocomm Research, A*STAR EKVLING@ntu.edu.sg Engineering::Electrical and electronic engineering For a drone to land precisely on a target in a flat terrain, it must accurately estimate its 4-dimensional (4D) position, which are the x-y-z coordinates and yaw orientation, with respect to its landing target. In this Final Year Project (FYP), we seek to investigate, adapt, and apply 4D pose estimation research for the purpose of drone landing on a ground robot in a flat terrain. A quadrotor and ground robot are simulated in a robot software environment in which the devised methodologies are implemented on the simulated drone to estimate its 4D pose with respect to the ground robot. The accuracy of the proposed implementation is measured by comparing the generated 4D pose estimates with the actual 4D pose values provided by the simulation. In an overview, the main methods used are deep learning for image points prediction, an efficient solution for the Perspective-N-Point (PNP) problem, and the Kalman filter for filtering / smoothening noisy estimates. These methods will be combined in tandem to form a pipeline for continuous pose estimation for the drone. In addition to this constructed pipeline, a section has been dedicated to exploratively address the problem of occlusion using Generative Adversarial Network, or in short GAN. Overall, the success of methods implemented within the simulation allows us to construct a proof-of-concept for 4D pose estimation on a real-life drone. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-17T01:51:58Z 2022-05-17T01:51:58Z 2022 Final Year Project (FYP) Hoo, S. J. (2022). Tracking and precise landing by a quadrotor. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158054 https://hdl.handle.net/10356/158054 en B1079-211 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Hoo, Shi Jan Tracking and precise landing by a quadrotor |
| title | Tracking and precise landing by a quadrotor |
| title_full | Tracking and precise landing by a quadrotor |
| title_fullStr | Tracking and precise landing by a quadrotor |
| title_full_unstemmed | Tracking and precise landing by a quadrotor |
| title_short | Tracking and precise landing by a quadrotor |
| title_sort | tracking and precise landing by a quadrotor |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/158054 |
| work_keys_str_mv | AT hooshijan trackingandpreciselandingbyaquadrotor |