인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
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.
피인용 0
초록·키워드
With the recent advancement of autonomous marine mobility, various studies have been conducted focusing on four modules of H/W and S/W architecture: localization, perception, decision/planning, and maneuvering/control. In marine mobility such as large ships and offshore structures, localization technique is often simply constructed solely using signals measured by Global Navigation and Satellite systems (GNSS). However, small autonomous marine mobility designed for surveillance and reconnaissance are developed with constraints on budget, size, and weight, as well as a high risk of loss during mission execution. In this paper, it was aimed to develop a localization technique applicable to small autonomous marine mobility considering a low-cost, low-precision GNSS with a 3D LiDAR point cloud. Furthermore, metrics were proposed for qualitative and indirect quantitative evaluation of the developed localization technique. First, a positioning technique was developed using an Extended Kalman filter (EKF) and Iterative Closest Point (ICP) map matching. Second, residuals were used for the qualitative evaluation of the developed localization technique. Third, the Intersection over Union (IoU) was used for indirect quantitative evaluation. Finally, it was confirmed that localization performance was significantly improved using the proposed indices.
본문·목차
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오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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