Monocular‐based collision avoidance system for unmanned aerial vehicle
Abstract Obstacle avoidance based on a monocular camera is a challenging task due to the lack of 3D information for Unmanned Aerial Vehicle. Recent methods based on Convolutional Neural Networks for monocular depth estimation and obstacle detection become widely used. However, collision avoidance wi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-03-01
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| Series: | IET Smart Cities |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/smc2.12067 |
| _version_ | 1797277234566791168 |
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| author | Abdulrahman Javaid Asaad Alduais M. Hashem Shullar Uthman Baroudi Mustafa Alnaser |
| author_facet | Abdulrahman Javaid Asaad Alduais M. Hashem Shullar Uthman Baroudi Mustafa Alnaser |
| author_sort | Abdulrahman Javaid |
| collection | DOAJ |
| description | Abstract Obstacle avoidance based on a monocular camera is a challenging task due to the lack of 3D information for Unmanned Aerial Vehicle. Recent methods based on Convolutional Neural Networks for monocular depth estimation and obstacle detection become widely used. However, collision avoidance with depth estimation usually suffers from long computational time and low avoidance success rate. A new collision avoidance system is proposed which uses monocular camera and intelligent algorithm to avoid obstacles on real time processing. Several experiments have been conducted on crowded environments with several object types. The results show outstanding performance in terms of obstacles avoidance and system response time compared to contemporary approaches. This makes the proposed approach of high potential to be integrated in crowded environments. |
| first_indexed | 2024-03-07T15:44:41Z |
| format | Article |
| id | doaj.art-9d143fbbf1db4c36b99c1c6523b0463a |
| institution | Directory Open Access Journal |
| issn | 2631-7680 |
| language | English |
| last_indexed | 2024-03-07T15:44:41Z |
| publishDate | 2024-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Smart Cities |
| spelling | doaj.art-9d143fbbf1db4c36b99c1c6523b0463a2024-03-05T04:49:33ZengWileyIET Smart Cities2631-76802024-03-01611910.1049/smc2.12067Monocular‐based collision avoidance system for unmanned aerial vehicleAbdulrahman Javaid0Asaad Alduais1M. Hashem Shullar2Uthman Baroudi3Mustafa Alnaser4Research and Development Department Yokogawa Saudi Arabia Company Al Khobar Saudi ArabiaDepartment of Electrical Engineering King Fahd University of Petroleum & Minerals Dhahran Saudi ArabiaDepartment of Electrical Engineering King Fahd University of Petroleum & Minerals Dhahran Saudi ArabiaDepartment of Computer Engineering King Fahd University of Petroleum & Minerals Dhahran Saudi ArabiaResearch and Development Department Yokogawa Saudi Arabia Company Al Khobar Saudi ArabiaAbstract Obstacle avoidance based on a monocular camera is a challenging task due to the lack of 3D information for Unmanned Aerial Vehicle. Recent methods based on Convolutional Neural Networks for monocular depth estimation and obstacle detection become widely used. However, collision avoidance with depth estimation usually suffers from long computational time and low avoidance success rate. A new collision avoidance system is proposed which uses monocular camera and intelligent algorithm to avoid obstacles on real time processing. Several experiments have been conducted on crowded environments with several object types. The results show outstanding performance in terms of obstacles avoidance and system response time compared to contemporary approaches. This makes the proposed approach of high potential to be integrated in crowded environments.https://doi.org/10.1049/smc2.12067data structures, artificial intelligence, data analytics and machine learningintelligent controlIoT and mobile communicationssmart cities applications |
| spellingShingle | Abdulrahman Javaid Asaad Alduais M. Hashem Shullar Uthman Baroudi Mustafa Alnaser Monocular‐based collision avoidance system for unmanned aerial vehicle IET Smart Cities data structures, artificial intelligence, data analytics and machine learning intelligent control IoT and mobile communications smart cities applications |
| title | Monocular‐based collision avoidance system for unmanned aerial vehicle |
| title_full | Monocular‐based collision avoidance system for unmanned aerial vehicle |
| title_fullStr | Monocular‐based collision avoidance system for unmanned aerial vehicle |
| title_full_unstemmed | Monocular‐based collision avoidance system for unmanned aerial vehicle |
| title_short | Monocular‐based collision avoidance system for unmanned aerial vehicle |
| title_sort | monocular based collision avoidance system for unmanned aerial vehicle |
| topic | data structures, artificial intelligence, data analytics and machine learning intelligent control IoT and mobile communications smart cities applications |
| url | https://doi.org/10.1049/smc2.12067 |
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