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A robust stereo camera localization method with prior LiDAR map constrains
Han,Dong1,2; Zou,Zuhao1; Wang,Lujia1; Xu,Cheng Zhong3
Source PublicationIEEE International Conference on Robotics and Biomimetics, ROBIO 2019
AbstractIn complex environments, low-cost and robust localization is a challenging problem. For example, in a GPS-denied environment, LiDAR can provide accurate position information, but the cost is high. In general, visual SLAM based localization methods become unreliable when the sunlight changes greatly. Therefore, inexpensive and reliable methods are required. In this paper, we propose a stereo visual localization method based on the prior LiDAR map. Different from the conventional visual localization system, we design a novel visual optimization model by matching planar information between the LiDAR map and visual image. Bundle adjustment is built by using coplanarity constraints. To solve the optimization problem, we use a graph-based optimization algorithm and a local window optimization method. Finally, we estimate a full six degrees of freedom (DOF) pose without scale drift. To validate the efficiency, the proposed method has been tested on the KITTI dataset. The results show that our method is more robust and accurate than the state-of-art ORB-SLAM2.
KeywordGlobal localization Point cloud Sensor fusion SLAM Stereo vision
URLView the original
Scopus ID2-s2.0-85079054933
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Document TypeConference paper
CollectionFaculty of Science and Technology
Affiliation1.Chinese Academy of Sciences,Shenzhen Institutes of Advanced Technology,Shenzhen,China
2.University of Chinese Academy of Sciences,China
3.University of Macau,Macao
Recommended Citation
GB/T 7714
Han,Dong,Zou,Zuhao,Wang,Lujia,et al. A robust stereo camera localization method with prior LiDAR map constrains[C],2019:2001-2006.
APA Han,Dong,Zou,Zuhao,Wang,Lujia,&Xu,Cheng Zhong.(2019).A robust stereo camera localization method with prior LiDAR map constrains.IEEE International Conference on Robotics and Biomimetics, ROBIO 2019,2001-2006.
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