Proceedings of the Korea Information Processing Society Conference (한국정보처리학회:학술대회논문집)
- 2018.10a
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- Pages.430-433
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- 2018
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- 2005-0011(pISSN)
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- 2671-7298(eISSN)
DOI QR Code
Velocity and Position Estimation of UAVs Based on Sensor Fusion and Kalman Filter
센서퓨전과 칼만필터에 기반한 무인항고기의 속도와 위치 추정
- Kang, Hyun-Ho (Dept. of Electrical Engineering, Korea University) ;
- Kim, Kwan-Soo (Dept. of Electrical Engineering, Korea University) ;
-
Lee, Sang-Su
(Dept. of Electrical Engineering, Korea University)
;
-
You, Sung-Hyun
(Dept. of Electrical Engineering, Korea University)
;
- Lee, Dhong-Hun (Dept. of Electrical Engineering, Korea University) ;
- Lee, Dong-Kyu (Dept. of Electrical Engineering, Korea University) ;
- Kim, Young-Eun (Dept. of Mechatronics, Korea University) ;
- Ahn, Choon-Ki (Dept. of Electrical Engineering, Korea University)
- 강현호 (고려대학교 전기전자공학과) ;
- 김관수 (고려대학교 전기전자공학과) ;
-
이상수
(고려대학교 전기전자공학과)
;
-
유성현
(고려대학교 전기전자공학과)
;
- 이동훈 (고려대학교 전기전자공학과) ;
- 이동규 (고려대학교 전기전자공학과) ;
- 김영은 (고려대학교 메카트로닉스) ;
- 안춘기 (고려대학교 전기전자공학과)
- Published : 2018.10.31
Abstract
This paper proposes the Kalman filter (KF) with optical flow method to estimate the position and the velocity of unmanned aerial vehicles (UAVs) in the absence of global positioning system (GPS). A downward-looking camera, a gyroscope and an ultrasonic sensor are fused to compensate the measurement from optical-flow method. To overcome the problem of dealing with noise in onboard sensors, the KF is incorporated to efficiently predict the velocity and estimate the position. Basic mechanisms of optical flow and the KF are introduced and experiments are conducted to show how the techniques involved improve the estimations.
Keywords