抄録
Determining unit position is very important for indoor autonomous aerial robots. In prior research, we used externally installed cameras to detect natural unit features to reduce the burden of measuring position, focusing on the elliptical trajectory of the rotating rotors while the unit was in flight as the natural feature of interest. Ellipse detection within images allows calculation of unit position. An outstanding problem is that ellipse detection takes a considerable amount of time, and in some environments it is difficult to distinguish between the rotor and the background. In this study, we investigate methods for addressing these problems, proposing a novel algorithm for fast ellipse detection. Furthermore, we record and visualize change in the rotating rotor pattern over time to enable detection against previously problematic backgrounds. For verification, we fly a general-purpose unit in a variety of environments and measure unit position. The results show that the proposed method reduces processing times for ellipse detection and that position can be measured without depending on the composition of flight environment, and thus that unit position detection is improved through the use of infrastructure cameras.
| 元の言語 | English |
|---|---|
| ジャーナル | IEEE Sensors Journal |
| DOI | |
| 出版物ステータス | Accepted/In press - 2018 1 1 |
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ASJC Scopus subject areas
- Instrumentation
- Electrical and Electronic Engineering
これを引用
Speed-up Automatic Quadcopter Position Detection by Sensing Propeller Rotation. / Premachandra, Chinthaka; Ueda, Daiki; Kato, Kiyotaka.
：: IEEE Sensors Journal, 01.01.2018.研究成果: Article
}
TY - JOUR
T1 - Speed-up Automatic Quadcopter Position Detection by Sensing Propeller Rotation
AU - Premachandra, Chinthaka
AU - Ueda, Daiki
AU - Kato, Kiyotaka
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Determining unit position is very important for indoor autonomous aerial robots. In prior research, we used externally installed cameras to detect natural unit features to reduce the burden of measuring position, focusing on the elliptical trajectory of the rotating rotors while the unit was in flight as the natural feature of interest. Ellipse detection within images allows calculation of unit position. An outstanding problem is that ellipse detection takes a considerable amount of time, and in some environments it is difficult to distinguish between the rotor and the background. In this study, we investigate methods for addressing these problems, proposing a novel algorithm for fast ellipse detection. Furthermore, we record and visualize change in the rotating rotor pattern over time to enable detection against previously problematic backgrounds. For verification, we fly a general-purpose unit in a variety of environments and measure unit position. The results show that the proposed method reduces processing times for ellipse detection and that position can be measured without depending on the composition of flight environment, and thus that unit position detection is improved through the use of infrastructure cameras.
AB - Determining unit position is very important for indoor autonomous aerial robots. In prior research, we used externally installed cameras to detect natural unit features to reduce the burden of measuring position, focusing on the elliptical trajectory of the rotating rotors while the unit was in flight as the natural feature of interest. Ellipse detection within images allows calculation of unit position. An outstanding problem is that ellipse detection takes a considerable amount of time, and in some environments it is difficult to distinguish between the rotor and the background. In this study, we investigate methods for addressing these problems, proposing a novel algorithm for fast ellipse detection. Furthermore, we record and visualize change in the rotating rotor pattern over time to enable detection against previously problematic backgrounds. For verification, we fly a general-purpose unit in a variety of environments and measure unit position. The results show that the proposed method reduces processing times for ellipse detection and that position can be measured without depending on the composition of flight environment, and thus that unit position detection is improved through the use of infrastructure cameras.
KW - Automatic quadcopter detection
KW - Cameras
KW - Image edge detection
KW - image substraction accumulation
KW - position determination
KW - Position measurement
KW - Robot vision systems
KW - Rotors
KW - speed-up ellipse detection
KW - Transforms
UR - http://www.scopus.com/inward/record.url?scp=85059017823&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059017823&partnerID=8YFLogxK
U2 - 10.1109/JSEN.2018.2888909
DO - 10.1109/JSEN.2018.2888909
M3 - Article
AN - SCOPUS:85059017823
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
SN - 1530-437X
ER -