This paper proposes a pose-graph based SLAM method using an upward-looking camera and artificial landmarks for AGVs in factory environments. The proposed method provides a way to acquire the camera extrinsic matrix and improves the accuracy of feature observation using a low-costcamera. SLAM is conducted by optimizing AGV’s explored path using the artificial landmarks installed on the ceiling at various locations. As the AGV explores, the pose nodes are added based on the certain distance from odometry and the landmark nodes are registered when AGV recognizes the fiducial marks. As a result of the proposed scheme, a graph network is created and optimized through a G2O optimization tool so that the accumulated error due to the slip is minimized. The experiment shows that the proposed method is robust for SLAM in real factory environments.

1. 서 론
 2. 천장 영상지도 작성
  2.1 영상 투영모델
  2.2 인공표식 인식을 통한 외부행렬 획득
 3. 천장 카메라 기반의 포즈그래프 SLAM
  3.1 AGV 위치 노드 및 에지 등록
  3.2 인공표식 인식을 통한 루프 인식
 4. 실험 및 결과
 5. 결 론
 References

• 허환(Mechatronics, Korea University) | Heo Hwan
• 송재복(Mechanical Engineering, Korea University, 145, Anam-ro, Seongbuk-gu, Seoul, Korea) | Song Jae-Bok Corresponding author