Online from: 1929
Subject Area: Mechanical & Materials Engineering
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|Title:||Obstacle avoidance for small UAVs using monocular vision|
|Author(s):||Jeong-Oog Lee, (Aerospace Information Engineering, Konkuk University, Seoul, Republic of Korea), Keun-Hwan Lee, (Aerospace Information Engineering, Konkuk University, Seoul, Republic of Korea), Sang-Heon Park, (Pohang Institute of Intelligent Robotics, Gyeongbuk, Republic of Korea), Sung-Gyu Im, (Aerospace Information Engineering, Konkuk University, Seoul, Republic of Korea), Jungkeun Park, (Aerospace Information Engineering, Konkuk University, Seoul, Republic of Korea)|
|Citation:||Jeong-Oog Lee, Keun-Hwan Lee, Sang-Heon Park, Sung-Gyu Im, Jungkeun Park, (2011) "Obstacle avoidance for small UAVs using monocular vision", Aircraft Engineering and Aerospace Technology, Vol. 83 Iss: 6, pp.397 - 406|
|Keywords:||Collisions, Image processing, Monocular vision, MOPS, Obstacle avoidance, SIFT algorithm, Small UAVs|
|Article type:||Research paper|
|DOI:||10.1108/00022661111173270 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
|Acknowledgements:||This paper was supported by Konkuk University in 2010.|
Purpose – The purpose of this paper is to propose that the three-dimensional information of obstacles should be identified to allow unmanned aerial vehicles (UAVs) to detect and avoid obstacles existing in their flight path.
Design/methodology/approach – First, the approximate outline of obstacles was detected using multi-scale-oriented patches (MOPS). At the same time, the spatial coordinates of feature points that exist in the internal outline of the obstacles were calculated through the scale-invariant feature transform (SIFT) algorithm. Finally, the results from MOPS and the results from the SIFT algorithm were merged to show the three-dimensional information of the obstacles.
Findings – As the method proposed in this paper reconstructs only the approximate outline of obstacles, a quick calculation can be done. Moreover, as the outline information is combined through SIFT feature points, detailed three-dimensional information pertaining to the obstacles can be obtained.
Practical implications – The proposed approach can be used efficiently in GPS-denied environments such as certain indoor environments.
Originality/value – For the autonomous flight of small UAVs having a payload limit, this paper suggests a means of forming three-dimensional information about obstacles with images obtained from a monocular camera.
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