Vision based artificial intelligence drone localization for swarm drone application
This report delves into the utilization of computer vision methods for localizing drones within a swarm formation, particularly in scenarios where communication between drones is disrupted or jammed, necessitating alternative localization techniques. Employing object detection, pose estimation, and...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/177550 |
| _version_ | 1811685033954508800 |
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| author | Cheng, Junius Zhen Yang |
| author2 | Li King Ho, Holden |
| author_facet | Li King Ho, Holden Cheng, Junius Zhen Yang |
| author_sort | Cheng, Junius Zhen Yang |
| collection | NTU |
| description | This report delves into the utilization of computer vision methods for localizing drones within a swarm formation, particularly in scenarios where communication between drones is disrupted or jammed, necessitating alternative localization techniques. Employing object detection, pose estimation, and other computer vision methodologies, the study aims to derive global coordinates crucial for directing drone movement. The primary objective is to devise a cost-effective algorithm applicable across all drones, with computational tasks centralized on a PC rather than the drones themselves. Central to this research is the exploration of visual sensors as a viable solution for drone localization in the absence of reliable communication channels. By addressing the challenges of jammed communication, this study seeks to establish a robust framework for drone localization within swarm formations, thereby enhancing coordination and resilience in drone operations. |
| first_indexed | 2024-10-01T04:38:06Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/177550 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:38:06Z |
| publishDate | 2024 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1775502024-06-01T16:52:51Z Vision based artificial intelligence drone localization for swarm drone application Cheng, Junius Zhen Yang Li King Ho, Holden School of Mechanical and Aerospace Engineering Temasek Laboratories @ NTU Ong Eng Hui HoldenLi@ntu.edu.sg Engineering Computer vision This report delves into the utilization of computer vision methods for localizing drones within a swarm formation, particularly in scenarios where communication between drones is disrupted or jammed, necessitating alternative localization techniques. Employing object detection, pose estimation, and other computer vision methodologies, the study aims to derive global coordinates crucial for directing drone movement. The primary objective is to devise a cost-effective algorithm applicable across all drones, with computational tasks centralized on a PC rather than the drones themselves. Central to this research is the exploration of visual sensors as a viable solution for drone localization in the absence of reliable communication channels. By addressing the challenges of jammed communication, this study seeks to establish a robust framework for drone localization within swarm formations, thereby enhancing coordination and resilience in drone operations. Bachelor's degree 2024-05-29T09:17:14Z 2024-05-29T09:17:14Z 2024 Final Year Project (FYP) Cheng, J. Z. Y. (2024). Vision based artificial intelligence drone localization for swarm drone application. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/177550 https://hdl.handle.net/10356/177550 en C126 application/pdf Nanyang Technological University |
| spellingShingle | Engineering Computer vision Cheng, Junius Zhen Yang Vision based artificial intelligence drone localization for swarm drone application |
| title | Vision based artificial intelligence drone localization for swarm drone application |
| title_full | Vision based artificial intelligence drone localization for swarm drone application |
| title_fullStr | Vision based artificial intelligence drone localization for swarm drone application |
| title_full_unstemmed | Vision based artificial intelligence drone localization for swarm drone application |
| title_short | Vision based artificial intelligence drone localization for swarm drone application |
| title_sort | vision based artificial intelligence drone localization for swarm drone application |
| topic | Engineering Computer vision |
| url | https://hdl.handle.net/10356/177550 |
| work_keys_str_mv | AT chengjuniuszhenyang visionbasedartificialintelligencedronelocalizationforswarmdroneapplication |