Object detection technique for small unmanned aerial vehicle
Obstacle detection and avoidance is desirable for UAVs especially lightweight micro aerial vehicles and is challenging problem since it has payload constraints, therefore only limited sensor can be attached the vehicle. Usually the sensors incorporated in the system is either type vision based (mono...
| Main Authors: | , , |
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| Format: | Proceeding Paper |
| Language: | English English English English |
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IOP
2017
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| Online Access: | http://irep.iium.edu.my/58901/ http://irep.iium.edu.my/58901/1/ICOM_2017_Ari%20Legowo.pdf http://irep.iium.edu.my/58901/7/58901_Object%20Detection%20Technique_tentative.pdf http://irep.iium.edu.my/58901/18/58901_Object%20detection%20technique.pdf http://irep.iium.edu.my/58901/24/58901%20Object%20detection%20technique%20for%20small%20unmanned%20aerial%20vehicle%20SCOPUS.pdf |
| _version_ | 1848785204115668992 |
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| author | Ramli, M. Faiz Legowo, Ari Shamsudin, Syariful Syafiq |
| author_facet | Ramli, M. Faiz Legowo, Ari Shamsudin, Syariful Syafiq |
| author_sort | Ramli, M. Faiz |
| building | IIUM Repository |
| collection | Online Access |
| description | Obstacle detection and avoidance is desirable for UAVs especially lightweight micro aerial vehicles and is challenging problem since it has payload constraints, therefore only limited sensor can be attached the vehicle. Usually the sensors incorporated in the system is either type vision based (monocular or stereo camera) or Laser based. However, each of the sensor has its own advantage and disadvantage, thus we built the obstacle detection and avoidance system based multi sensor (monocular sensor and LIDAR) integration. On top of that, we also combine SURF algorithm with Harris corner detector to determine the approximate size of the obstacles. In the initial experiment conducted, we successfully detect and determine the size of the obstacles with 3 different obstacles. The differences of length between real obstacles and our algorithm are considered acceptable which is about -0.4 to 3.6. |
| first_indexed | 2025-11-14T16:49:25Z |
| format | Proceeding Paper |
| id | iium-58901 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English English English |
| last_indexed | 2025-11-14T16:49:25Z |
| publishDate | 2017 |
| publisher | IOP |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-589012018-03-23T02:17:39Z http://irep.iium.edu.my/58901/ Object detection technique for small unmanned aerial vehicle Ramli, M. Faiz Legowo, Ari Shamsudin, Syariful Syafiq TL500 Aeronautics Obstacle detection and avoidance is desirable for UAVs especially lightweight micro aerial vehicles and is challenging problem since it has payload constraints, therefore only limited sensor can be attached the vehicle. Usually the sensors incorporated in the system is either type vision based (monocular or stereo camera) or Laser based. However, each of the sensor has its own advantage and disadvantage, thus we built the obstacle detection and avoidance system based multi sensor (monocular sensor and LIDAR) integration. On top of that, we also combine SURF algorithm with Harris corner detector to determine the approximate size of the obstacles. In the initial experiment conducted, we successfully detect and determine the size of the obstacles with 3 different obstacles. The differences of length between real obstacles and our algorithm are considered acceptable which is about -0.4 to 3.6. IOP 2017-08-08 Proceeding Paper NonPeerReviewed application/pdf en http://irep.iium.edu.my/58901/1/ICOM_2017_Ari%20Legowo.pdf application/pdf en http://irep.iium.edu.my/58901/7/58901_Object%20Detection%20Technique_tentative.pdf application/pdf en http://irep.iium.edu.my/58901/18/58901_Object%20detection%20technique.pdf application/pdf en http://irep.iium.edu.my/58901/24/58901%20Object%20detection%20technique%20for%20small%20unmanned%20aerial%20vehicle%20SCOPUS.pdf Ramli, M. Faiz and Legowo, Ari and Shamsudin, Syariful Syafiq (2017) Object detection technique for small unmanned aerial vehicle. In: 6th International Conference on Mechatronics (ICOM'17), 8th-9th August 2017, Kuala Lumpur. http://www.iium.edu.my/icom/ |
| spellingShingle | TL500 Aeronautics Ramli, M. Faiz Legowo, Ari Shamsudin, Syariful Syafiq Object detection technique for small unmanned aerial vehicle |
| title | Object detection technique for small unmanned aerial vehicle |
| title_full | Object detection technique for small unmanned aerial vehicle |
| title_fullStr | Object detection technique for small unmanned aerial vehicle |
| title_full_unstemmed | Object detection technique for small unmanned aerial vehicle |
| title_short | Object detection technique for small unmanned aerial vehicle |
| title_sort | object detection technique for small unmanned aerial vehicle |
| topic | TL500 Aeronautics |
| url | http://irep.iium.edu.my/58901/ http://irep.iium.edu.my/58901/ http://irep.iium.edu.my/58901/1/ICOM_2017_Ari%20Legowo.pdf http://irep.iium.edu.my/58901/7/58901_Object%20Detection%20Technique_tentative.pdf http://irep.iium.edu.my/58901/18/58901_Object%20detection%20technique.pdf http://irep.iium.edu.my/58901/24/58901%20Object%20detection%20technique%20for%20small%20unmanned%20aerial%20vehicle%20SCOPUS.pdf |