The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Implementation of Bayesian Filter Method and Range Measurement Analysis for Underwater Robot Localization

수중로봇 위치추정을 위한 베이시안 필터 방법의 실현과 거리 측정 특성 분석

  • Noh, Sung Woo (Information and Communication Engineering, Chosun University) ;
  • Ko, Nak Yong (Dept. Control, Instrumentation and Robot Engineering, Chosun University) ;
  • Kim, Tae Gyun (Ocean System Engineering Research Division, KIOST)
  • Received : 2013.11.07
  • Accepted : 2014.02.14
  • Published : 2014.02.28
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Abstract

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.

Keywords

References

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