Safe avoidance path detection using multi sensor integration for small unmanned aerial vehicle
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...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English English English English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2018
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| Subjects: | |
| Online Access: | 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 |
| Summary: | 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. |
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