수중로봇 위치추정을 위한 베이시안 필터 방법의 실현과 거리 측정 특성 분석
Implementation of Bayesian Filter Method and Range Measurement Analysis for Underwater Robot Localization
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초록
This paper verifies the performance of Extended Kalman Filter(EKF) and MCL(MonteCarlo Localization) approach to localization of an underwater vehicle through experiments. Especially, the experiments use acoustic range sensor whose measurement accuracy and uncertainty isnot yet proved. Along with localization, the experiment also discloses the uncertainty features of therange measurement such as bias and variance. The proposed localization method rejects outlier rangedata and the experiment shows that outlier rejection improves localization performance. It is asexpected that the proposed method doesn’t yield as precise location as those methods which use highpriced DVL(Doppler Velocity Log), IMU(Inertial Measurement Unit), and high accuracy rangesensors. However, it is noticeable that the proposed method can achieve the accuracy which isaffordable for correction of accumulated dead reckoning error, even though it uses only range data oflow reliability and accuracy.
Abstract
This paper verifies the performance of Extended Kalman Filter(EKF) and MCL(MonteCarlo Localization) approach to localization of an underwater vehicle through experiments. Especially, the experiments use acoustic range sensor whose measurement accuracy and uncertainty isnot yet proved. Along with localization, the experiment also discloses the uncertainty features of therange measurement such as bias and variance. The proposed localization method rejects outlier rangedata and the experiment shows that outlier rejection improves localization performance. It is asexpected that the proposed method doesn’t yield as precise location as those methods which use highpriced DVL(Doppler Velocity Log), IMU(Inertial Measurement Unit), and high accuracy rangesensors. However, it is noticeable that the proposed method can achieve the accuracy which isaffordable for correction of accumulated dead reckoning error, even though it uses only range data oflow reliability and accuracy.
참고문헌 (15)
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