공장환경에서 AGV를 위한 인공표식 기반의 포즈그래프 SLAM
Artificial Landmark based Pose-Graph SLAM for AGVs in Factory Environments
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초록
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-cost camera. 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.
Abstract
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-cost camera. 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.
참고문헌 (7)
- 정민국, "센서 융합을 통한 환경지도 기반의 강인한 전역 위치추정", 로봇학회 논문지, 9(2), pp.96~103 (2014), 한국로봇학회[DOI]
- 허환, "천장 영상지도 기반의 전역 위치추정", 로봇학회 논문지, 9(3), pp.170~177 (2014), 한국로봇학회
- T. Bailey, "Consistency of the EKF-SLAM Algorithm", IEEE, 2006, ~
- J. L. Martinez, "Mobile Robot Motion Estimation by 2D Scan Matching with Genetic and Iterative Closest Point Algorithms", Journal of Field Robotics, 23(1), pp.21~34 (2006)
- M. Cummins, "FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance", Int. Journal of Robotics Research, 27(6), pp.647~665 (2008)
- D. ronzoni, "AGV Global Localization Using Indistinguishable Artificial Landmarks", Int. Conf. on Robotics and Automation, pp.287~292 (2011)
- Kummerle, R., "g2og2o: A General Framework for Graph Optimization", Int. Conf. on Robotics and Automations, pp.3607~3613 (2011)