The Journal of Korea Robotics Society (로봇학회논문지)
- Volume 3 Issue 3
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- Pages.176-185
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- 2008
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- 1975-6291(pISSN)
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- 2287-3961(eISSN)
New Filtering Method for Reducing Registration Error of Distributed Sensors
분산된 센서들의 Registration 오차를 줄이기 위한 새로운 필터링 방법
- Kim, Yong-Shik ;
- Lee, Jae-Hoon ;
- Do, Hyun-Min ;
- Kim, Bong-Keun ;
- Tanikawa, Tamio ;
- Ohba, Kohtaro ;
- Lee, Ghang ;
- Yun, Seok-Heon
- 김용식 (일본 AIST UFRG 연구원) ;
- 이재훈 (일본 AIST UFRG 연구원) ;
- 도현민 (일본 AIST UFRG 연구원) ;
- 김봉근 (일본 AIST UFRG 연구원) ;
- 타니카와 타미오 (일본 AIST UFRG 연구원) ;
- 오바 코타로 (일본 AIST UFRG 연구원) ;
- 이강 (연세대학교 건축공학과) ;
- 윤석헌 (경상대학교 건축학부)
- Published : 2008.08.29
Abstract
In this paper, new filtering method for sensor registration is provided to estimate and correct error of registration parameters in multiple sensor environments. Sensor registration is based on filtering method to estimate registration parameters in multiple sensor environments. Accuracy of sensor registration can increase performance of data fusion method selected. Due to various error sources, the sensor registration has registration errors recognized as multiple objects even though multiple sensors are tracking one object. In order to estimate the error parameter, new nonlinear information filtering method is developed using minimum mean square error estimation. Instead of linearization of nonlinear function like an extended Kalman filter, information estimation through unscented prediction is used. The proposed method enables to reduce estimation error without a computation of the Jacobian matrix in case that measurement dimension is large. A computer simulation is carried out to evaluate the proposed filtering method with an extended Kalman filter.
Keywords