검색결과

검색조건
좁혀보기
검색필터
결과 내 재검색

간행물

    분야

      발행연도

      -

        검색결과 3

        1.
        2002.12 KCI 등재 SCOPUS 구독 인증기관 무료, 개인회원 유료
        4,800원
        2.
        2002.03 KCI 등재 SCOPUS 구독 인증기관 무료, 개인회원 유료
        5,700원
        3.
        2019.06 KCI 등재 서비스 종료(열람 제한)
        This paper presents a 6-DOF relocalization using a 3D laser scanner and a monocular camera. A relocalization problem in robotics is to estimate pose of sensor when a robot revisits the area. A deep convolutional neural network (CNN) is designed to regress 6-DOF sensor pose and trained using both RGB image and 3D point cloud information in end-to-end manner. We generate the new input that consists of RGB and range information. After training step, the relocalization system results in the pose of the sensor corresponding to each input when a new input is received. However, most of cases, mobile robot navigation system has successive sensor measurements. In order to improve the localization performance, the output of CNN is used for measurements of the particle filter that smooth the trajectory. We evaluate our relocalization method on real world datasets using a mobile robot platform.