Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle

Achieving a robust obstacle detection system for small UAV is very challenging. Due to size and weight constraints, very limited detection sensors can be equipped in the system. Prior works focused on a single sensing device which is either camera or range sensors based. However, these sensors hav...

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Main Authors: Ramli, Muhammad Faiz, Shamsudin, Syariful Syafiq, Legowo, Ari
Format: Article
Language:English
English
Published: Institute of Advanced Engineering and Science (IAES) 2017
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Online Access:http://irep.iium.edu.my/62993/1/62993_Obstacle%20detection%20technique%20using%20multi%20sensor_article.pdf
http://irep.iium.edu.my/62993/2/62993_Obstacle%20detection%20technique%20using%20multi%20sensor_scopus.pdf
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http://www.iaescore.com/journals/index.php/IJEECS/article/view/10012/7647
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Institution: Universiti Islam Antarabangsa Malaysia
Language: English
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spelling my.iium.irep.629932018-03-23T03:18:55Z http://irep.iium.edu.my/62993/ Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle Ramli, Muhammad Faiz Shamsudin, Syariful Syafiq Legowo, Ari QA Mathematics TD Environmental technology. Sanitary engineering TJ Mechanical engineering and machinery Achieving a robust obstacle detection system for small UAV is very challenging. Due to size and weight constraints, very limited detection sensors can be equipped in the system. Prior works focused on a single sensing device which is either camera or range sensors based. However, these sensors have their own advantages and disadvantages in detecting the appearance of the obstacles. In this paper, combination of both sensors based is proposed for a small UAV obstacle detection system. A small Lidar sensor is used as the initial detector and queue for image capturing by the camera. Next, SURF algorithm is applied to find the obstacle sizes estimation by searching the connecting feature points in the image frame. Finally, safe avoidance path for UAV is determined through the exterior feature points from the estimated width of the obstacle. The proposed method was evaluated by conducting experiments in real time with indoor environment. In the experiment conducted, we successfully detect and determine a safe avoidance path for the UAV on 6 different sizes and textures of the obstacles including textureless obstacles Institute of Advanced Engineering and Science (IAES) 2017-11 Article REM application/pdf en http://irep.iium.edu.my/62993/1/62993_Obstacle%20detection%20technique%20using%20multi%20sensor_article.pdf application/pdf en http://irep.iium.edu.my/62993/2/62993_Obstacle%20detection%20technique%20using%20multi%20sensor_scopus.pdf Ramli, Muhammad Faiz and Shamsudin, Syariful Syafiq and Legowo, Ari (2017) Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle. Indonesian Journal of Electrical Engineering and Computer Science, 8 (2). pp. 441-449. ISSN 2502-4752 http://www.iaescore.com/journals/index.php/IJEECS/article/view/10012/7647 10.11591/ijeecs.v8.i2.pp441-449
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic QA Mathematics
TD Environmental technology. Sanitary engineering
TJ Mechanical engineering and machinery
spellingShingle QA Mathematics
TD Environmental technology. Sanitary engineering
TJ Mechanical engineering and machinery
Ramli, Muhammad Faiz
Shamsudin, Syariful Syafiq
Legowo, Ari
Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle
description Achieving a robust obstacle detection system for small UAV is very challenging. Due to size and weight constraints, very limited detection sensors can be equipped in the system. Prior works focused on a single sensing device which is either camera or range sensors based. However, these sensors have their own advantages and disadvantages in detecting the appearance of the obstacles. In this paper, combination of both sensors based is proposed for a small UAV obstacle detection system. A small Lidar sensor is used as the initial detector and queue for image capturing by the camera. Next, SURF algorithm is applied to find the obstacle sizes estimation by searching the connecting feature points in the image frame. Finally, safe avoidance path for UAV is determined through the exterior feature points from the estimated width of the obstacle. The proposed method was evaluated by conducting experiments in real time with indoor environment. In the experiment conducted, we successfully detect and determine a safe avoidance path for the UAV on 6 different sizes and textures of the obstacles including textureless obstacles
format Article
author Ramli, Muhammad Faiz
Shamsudin, Syariful Syafiq
Legowo, Ari
author_facet Ramli, Muhammad Faiz
Shamsudin, Syariful Syafiq
Legowo, Ari
author_sort Ramli, Muhammad Faiz
title Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle
title_short Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle
title_full Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle
title_fullStr Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle
title_full_unstemmed Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle
title_sort obstacle detection technique using multi sensor integration for small unmanned aerial vehicle
publisher Institute of Advanced Engineering and Science (IAES)
publishDate 2017
url http://irep.iium.edu.my/62993/1/62993_Obstacle%20detection%20technique%20using%20multi%20sensor_article.pdf
http://irep.iium.edu.my/62993/2/62993_Obstacle%20detection%20technique%20using%20multi%20sensor_scopus.pdf
http://irep.iium.edu.my/62993/
http://www.iaescore.com/journals/index.php/IJEECS/article/view/10012/7647
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