id iium-69114
recordtype eprints
spelling iium-691142019-01-02T01:07:59Z http://irep.iium.edu.my/69114/ Safe avoidance path detection using multi sensor integration for small unmanned aerial vehicle Ramli, Muhammad Faiz Shamsudin, Syariful Syafiq Legowo, Ari TE210 Construction details. Including foundation, maintenance, equipment TJ Mechanical engineering and machinery TJ210.2 Mechanical devices and figures. Automata. Ingenious mechanism. Robots (General) Achieving a robust obstacle detection system that can provide a safe avoidance path 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, a combination of both sensors based is proposed for a small UAV obstacle detection system. A small Lidar sensor is used as the initial detector of obstacle and queue for image capturing by the camera. Next, SURF 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 method was evaluated by conducting experiments in a real complex environment which consist of a textured and textureless obstacle. In the experiment conducted, we successfully detect and create a safe avoidance path for both situations. The textured situation gives a high success rate while textureless situation produces acceptable success rate until 60cm distance. Institute of Electrical and Electronics Engineers Inc. 2018-08-31 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/69114/3/69114_Safe%20avoidance%20path%20detection%20using%20multi%20sensor_cp.pdf application/pdf en http://irep.iium.edu.my/69114/4/69114_Safe%20avoidance%20path%20detection%20using%20multi%20sensor_scedule.pdf application/pdf en http://irep.iium.edu.my/69114/1/69114_Safe%20avoidance%20path%20detection%20using%20multi%20sensor_article.pdf application/pdf en http://irep.iium.edu.my/69114/2/69114_Safe%20avoidance%20path%20detection%20using%20multi%20sensor_scopus.pdf Ramli, Muhammad Faiz and Shamsudin, Syariful Syafiq and Legowo, Ari (2018) Safe avoidance path detection using multi sensor integration for small unmanned aerial vehicle. In: 5th IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2018, 20 - 22 June 2018, Rome; Italy. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8453521 10.1109/MetroAeroSpace.2018.8453521
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
English
English
English
topic TE210 Construction details. Including foundation, maintenance, equipment
TJ Mechanical engineering and machinery
TJ210.2 Mechanical devices and figures. Automata. Ingenious mechanism. Robots (General)
spellingShingle TE210 Construction details. Including foundation, maintenance, equipment
TJ Mechanical engineering and machinery
TJ210.2 Mechanical devices and figures. Automata. Ingenious mechanism. Robots (General)
Ramli, Muhammad Faiz
Shamsudin, Syariful Syafiq
Legowo, Ari
Safe avoidance path detection using multi sensor integration for small unmanned aerial vehicle
description Achieving a robust obstacle detection system that can provide a safe avoidance path 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, a combination of both sensors based is proposed for a small UAV obstacle detection system. A small Lidar sensor is used as the initial detector of obstacle and queue for image capturing by the camera. Next, SURF 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 method was evaluated by conducting experiments in a real complex environment which consist of a textured and textureless obstacle. In the experiment conducted, we successfully detect and create a safe avoidance path for both situations. The textured situation gives a high success rate while textureless situation produces acceptable success rate until 60cm distance.
format Conference or Workshop Item
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 Safe avoidance path detection using multi sensor integration for small unmanned aerial vehicle
title_short Safe avoidance path detection using multi sensor integration for small unmanned aerial vehicle
title_full Safe avoidance path detection using multi sensor integration for small unmanned aerial vehicle
title_fullStr Safe avoidance path detection using multi sensor integration for small unmanned aerial vehicle
title_full_unstemmed Safe avoidance path detection using multi sensor integration for small unmanned aerial vehicle
title_sort safe avoidance path detection using multi sensor integration for small unmanned aerial vehicle
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2018
url http://irep.iium.edu.my/69114/
http://irep.iium.edu.my/69114/
http://irep.iium.edu.my/69114/
http://irep.iium.edu.my/69114/3/69114_Safe%20avoidance%20path%20detection%20using%20multi%20sensor_cp.pdf
http://irep.iium.edu.my/69114/4/69114_Safe%20avoidance%20path%20detection%20using%20multi%20sensor_scedule.pdf
http://irep.iium.edu.my/69114/1/69114_Safe%20avoidance%20path%20detection%20using%20multi%20sensor_article.pdf
http://irep.iium.edu.my/69114/2/69114_Safe%20avoidance%20path%20detection%20using%20multi%20sensor_scopus.pdf
first_indexed 2023-09-18T21:38:06Z
last_indexed 2023-09-18T21:38:06Z
_version_ 1777412956332490752