Safe avoidance region detection for unmanned aerial vehicle using cues from expansion of feature points
Develop an obstacle detection system for Unmanned Aerial Vehicle (UAV) especially for small UAV is challenging. A robust system should be able to not only detect obstacles but the free region for the avoidance path as well. Besides, the configuration of the obstacles in the operating environment...
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| Format: | Conference or Workshop Item |
| Language: | en |
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2024
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| Online Access: | http://eprints.uthm.edu.my/12321/1/P17244_ed32f932361f3f44258076cdc977db34.pdf%209.pdf http://eprints.uthm.edu.my/12321/ |
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| _version_ | 1833419763713310720 |
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| author | Ramli, Muhammad Faiz Sutjipto, Agus G.E. Sulaeman, Erwin Ari Legowo, Ari Legowo |
| author_facet | Ramli, Muhammad Faiz Sutjipto, Agus G.E. Sulaeman, Erwin Ari Legowo, Ari Legowo |
| author_sort | Ramli, Muhammad Faiz |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Develop an obstacle detection system for Unmanned Aerial Vehicle (UAV) especially for
small UAV is challenging. A robust system should be able to not only detect obstacles but the free
region for the avoidance path as well. Besides, the configuration of the obstacles in the operating
environment should never be disregard. In this paper, expansion cues from the detected feature points
with the help of convex hull will be used to categorize the regions in the image frame. A micro LIDAR
sensor is used as the initial detector of obstacle and queue for image capturing by the camera. Next,
ORB algorithm is applied to find the obstacle regions and free space regions. This is done through
the principal of object size changes and distance relationship in an image perspective. The proposed
system was evaluated through series of experiments in a real environment which consist of different
configuration of obstacles. The experiments show the proposed system was able to find the safe
avoidance region regardless of the configuration of the obstacles in the operating environment.c |
| format | Conference or Workshop Item |
| id | my.uthm.eprints-12321 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2024 |
| record_format | eprints |
| spelling | my.uthm.eprints-123212025-05-28T00:22:13Z http://eprints.uthm.edu.my/12321/ Safe avoidance region detection for unmanned aerial vehicle using cues from expansion of feature points Ramli, Muhammad Faiz Sutjipto, Agus G.E. Sulaeman, Erwin Ari Legowo, Ari Legowo TL Motor vehicles. Aeronautics. Astronautics Develop an obstacle detection system for Unmanned Aerial Vehicle (UAV) especially for small UAV is challenging. A robust system should be able to not only detect obstacles but the free region for the avoidance path as well. Besides, the configuration of the obstacles in the operating environment should never be disregard. In this paper, expansion cues from the detected feature points with the help of convex hull will be used to categorize the regions in the image frame. A micro LIDAR sensor is used as the initial detector of obstacle and queue for image capturing by the camera. Next, ORB algorithm is applied to find the obstacle regions and free space regions. This is done through the principal of object size changes and distance relationship in an image perspective. The proposed system was evaluated through series of experiments in a real environment which consist of different configuration of obstacles. The experiments show the proposed system was able to find the safe avoidance region regardless of the configuration of the obstacles in the operating environment.c 2024 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/12321/1/P17244_ed32f932361f3f44258076cdc977db34.pdf%209.pdf Ramli, Muhammad Faiz and Sutjipto, Agus G.E. and Sulaeman, Erwin and Ari Legowo, Ari Legowo (2024) Safe avoidance region detection for unmanned aerial vehicle using cues from expansion of feature points. In: CONFERENCE ON INDUSTRIAL SCIENCES, ENGINEERING AND TECHNOLOGY TOWARD DIGITAL ERA (EICISET 2023). |
| spellingShingle | TL Motor vehicles. Aeronautics. Astronautics Ramli, Muhammad Faiz Sutjipto, Agus G.E. Sulaeman, Erwin Ari Legowo, Ari Legowo Safe avoidance region detection for unmanned aerial vehicle using cues from expansion of feature points |
| title | Safe avoidance region detection for unmanned aerial vehicle using cues from expansion of feature points |
| title_full | Safe avoidance region detection for unmanned aerial vehicle using cues from expansion of feature points |
| title_fullStr | Safe avoidance region detection for unmanned aerial vehicle using cues from expansion of feature points |
| title_full_unstemmed | Safe avoidance region detection for unmanned aerial vehicle using cues from expansion of feature points |
| title_short | Safe avoidance region detection for unmanned aerial vehicle using cues from expansion of feature points |
| title_sort | safe avoidance region detection for unmanned aerial vehicle using cues from expansion of feature points |
| topic | TL Motor vehicles. Aeronautics. Astronautics |
| url | http://eprints.uthm.edu.my/12321/1/P17244_ed32f932361f3f44258076cdc977db34.pdf%209.pdf http://eprints.uthm.edu.my/12321/ |
| url_provider | http://eprints.uthm.edu.my/ |