상세정보
학술지
어안 이미지 기반의 움직임 추정 기법을 이용한 전방향 영상 SLAM
- 저자
- 최윤원, 최정원, 대염염, 이석규
- 발행일
- 201408
- 출처
- 제어로봇시스템학회논문지, v.20 no.8, pp.868-874
- ISSN
- 1976-5622
- 출판사
- 제어로봇시스템학회
- 협약과제
- 14ZC2400, 상황인지 스마트카를위한 다중 센서 플랫폼기술개발, 권기구
- 초록
- This paper proposes a novel mapping algorithm in Omni-directional Vision SLAM based on an obstacle’s feature extraction using Lucas-Kanade Optical Flow motion detection and images obtained through fish-eye lenses mounted on robots. Omni-directional image sensors have distortion problems because they use a fish-eye lens or mirror, but it is possible in real time image processing for mobile robots because it measured all information around the robot at one time. In previous Omni-Directional Vision SLAM research, feature points in corrected fisheye images were used but the proposed algorithm corrected only the feature point of the obstacle. We obtained faster processing than previous systems through this process. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous 360° panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we remove the feature points of the floor surface using a histogram filter, and label the candidates of the obstacle extracted. Third, we estimate the location of obstacles based on motion vectors using LKOF. Finally, it estimates the robot position using an Extended Kalman Filter based on the obstacle position obtained by LKOF and creates a map. We will confirm the reliability of the mapping algorithm using motion estimation based on fisheye images through the comparison between maps obtained using the proposed algorithm and real maps.
- KSP 제안 키워드
- Extended kalman fiLTEr, Feature extractioN, Fisheye images, Floor surface, Image Sensor, Lucas-Kanade optical flow, Mapping algorithm, Mobile robots, Motion Vector(MV), Motion detection, Motion estimation(ME)