Abstract
This work presents a vision based navigation system for an autonomous drone that is capable of recognizing and locating wind mills. WindMillNet, a Deep Neural Network created for this purpose was specially trained to recognize wind mills on camera images using transfer learning techniques. The drone powered by WindMillNet scans the horizon to find wind mills, and after perceiving a wind mill, navigates towards it, with the goal of performing its inspection. A hierarchical control system, implemented in the drone provides stability and control of its movements. Our framework was designed using a cyber-physical systems approach using high-level abstractions in modeling, communication, control and computation.
Original language | English |
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Book series | IFAC-PapersOnLine |
Volume | 52 |
Issue number | 8 |
Pages (from-to) | 61-66 |
Number of pages | 6 |
ISSN | 1474-6670 |
DOIs | |
Publication status | Published - Jul 2019 |
Event | IFAC Symposium Intelligent Autonomous Vehicles - 10th IAV 2019 - Gdansk, Poland Duration: 3 Jul 2019 → 5 Jul 2019 http://www.konsulting.gda.pl/iav2019/web/ |
Conference
Conference | IFAC Symposium Intelligent Autonomous Vehicles - 10th IAV 2019 |
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Country/Territory | Poland |
City | Gdansk |
Period | 03/07/2019 → 05/07/2019 |
Internet address |
Keywords
- UAV
- Control
- Artificial Intelligence
- Vision
- Neural Networks
- Deep Learning
- Machine Learning