로봇학회논문지 (The Journal of Korea Robotics Society)

  • 제16권4호
  • /
  • Pages.306-312
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  • 2021
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  • 1975-6291(pISSN)
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  • 2287-3961(eISSN)
한국로봇학회 (Korea Robotics Society)
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병렬 학습 모듈을 통한 자율무인잠수정의 강인한 위치 추정

Robust AUV Localization Incorporating Parallel Learning Module

  • 투고 : 2021.09.28
  • 심사 : 2021.11.19
  • 발행 : 2021.11.30
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초록

This paper describes localization of autonomous underwater vehicles(AUV), which can be used when some navigation sensor data are an outlier. In that situation, localization through existing navigation algorithms causes problems in long-range localization. Even if an outlier sensor data occurs once, problems of localization will continue. Also, if outlier sensor data is related to azimuth (direction of AUV), it causes bigger problems. Therefore, a parallel localization module, in which different algorithms are performed in a normal and abnormal situation should be designed. Before designing a parallel localization module, it is necessary to study an effective method in the abnormal situation. So, we propose a localization method through machine learning. For this method, a learning model consists of only Fully-Connected and trains through randomly contaminated real sea data. The ground truth of training is displacement between subsequent GPS data. As a result, average error in localization through the learning model is 0.4 times smaller than the average error in localization through the existing navigation algorithm. Through this result, we conclude that it is suitable for a component of the parallel localization module.

키워드

과제정보

This research was supported by Institute of Civil Military Technology Cooperation (ICMTC) of Agency for Defense Development (ADD), funded by Defense Acquisition Program Administration (DAPA) and Ministry of Trade, Industry and Energy (MOTIE), (project titled as "Development of multi-sensor fusion based AUV's terminal guidance and docking technology")

참고문헌

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