지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2014.3
- 수록면
- 28 - 38 (11page)
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초록· 키워드
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This paper verifies the performance of Extended Kalman Filter(EKF) and MCL(Monte Carlo Localization) approach to localization of an underwater vehicle through experiments. Especially, the experiments use acoustic range sensor whose measurement accuracy and uncertainty is not yet proved. Along with localization, the experiment also discloses the uncertainty features of the range measurement such as bias and variance. The proposed localization method rejects outlier range data and the experiment shows that outlier rejection improves localization performance. It is as expected that the proposed method doesn’t yield as precise location as those methods which use high priced DVL(Doppler Velocity Log), IMU(Inertial Measurement Unit), and high accuracy range sensors. However, it is noticeable that the proposed method can achieve the accuracy which is affordable for correction of accumulated dead reckoning error, even though it uses only range data of low reliability and accuracy.
목차
Abstract
1. 서론
2. 수중 로봇 위치추정 방법
3. 실험 및 고찰
4. 결론
References
참고문헌 (15)
참고문헌 신청
1. [학술지(정기간행물)] - S. B Williams / 2012 / Monitoring of Benthic Reference Sites Using an Autonomous Underwater Vehicle / IEEE Robotics & Automation Magazine 19 (1) : 73 ~ 84
2. [단행본] - J. Borenstein / 1996 / Navigating Mobile Robots: Sensors and Techniques / AK Peters
3. [학술지(정기간행물)] - S. Julier / 2000 / A New Method for the Nonlinear Transformation of Means and Covariances in Filters and Estimators / IEEE Trans. on Automatic Control 45 (3) : 477 ~ 482
4. [학위논문] - R. van der Merwe / 2004 / Sigma-point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models / 박사 / Oregon Health & Science University
5. [학술지(정기간행물)] - N. Gordon / 1993 / Novel Approach to Nonlinear/Non-Gaussian Bayesian State Estimation / IEEE Proc. Radar and Signal Processing 140 (2) : 107 ~ 113
2. [단행본] - J. Borenstein / 1996 / Navigating Mobile Robots: Sensors and Techniques / AK Peters
3. [학술지(정기간행물)] - S. Julier / 2000 / A New Method for the Nonlinear Transformation of Means and Covariances in Filters and Estimators / IEEE Trans. on Automatic Control 45 (3) : 477 ~ 482
4. [학위논문] - R. van der Merwe / 2004 / Sigma-point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models / 박사 / Oregon Health & Science University
5. [학술지(정기간행물)] - N. Gordon / 1993 / Novel Approach to Nonlinear/Non-Gaussian Bayesian State Estimation / IEEE Proc. Radar and Signal Processing 140 (2) : 107 ~ 113
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UCI(KEPA) : I410-ECN-0101-2020-559-001258406