Abstract
This paper presents a novel approach based on deep neural networks for autonomous navigation of a quad-copter UAV in a sparsely populated environment. Images from the video camera mounted on the UAV are split, emulating a compounded eye, and processed by deep neural networks that calculate the probability that each image contains a wind turbine object. Then, these probabilities are used as inputs to a vision servoing system that controls the drone’s navigation movements. Our experiments show that our approach produces relatively stable movements in the UAV, allowing it to find and navigate autonomously towards a wind turbine.
Original language | English |
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Title of host publication | 15th European Workshop on Advanced Control and Diagnosis |
Number of pages | 15 |
Publisher | Springer |
Publication date | 17 Jun 2022 |
Pages | 1257-1272 |
ISBN (Electronic) | 978-3-030-85318-1 |
DOIs | |
Publication status | Published - 17 Jun 2022 |
Event | 15th European Workshop on Advanced Control and Diagnosis - Bologna, Italy Duration: 21 Nov 2019 → 22 Nov 2019 https://eventi.unibo.it/acd2019 |
Conference
Conference | 15th European Workshop on Advanced Control and Diagnosis |
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Country/Territory | Italy |
City | Bologna |
Period | 21/11/2019 → 22/11/2019 |
Internet address |
Series | Lecture Notes in Control and Information Sciences - Proceedings |
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ISSN | 2522-5383 |
Keywords
- Quad-copter UAV
- Control
- Visual Servoing
- Compounded Eye
- Artificial Intelligence
- Vision
- Machine Learning
- Robotics
- Deep Learing