Globally optimal consensus maximization for robust visual inertial localization in point and line map
Yanmei Jiao,Yue Wang,Bo Fu,Qimeng Tan,Lei Chen,Minhang Wang,Shoudong Huang,Rong Xiong,Yanmei Jiao,Yue Wang,Bo Fu,Qimeng Tan,Lei Chen,Minhang Wang,Shoudong Huang,Rong Xiong
Map based visual inertial localization is a crucial step to reduce the drift in state estimation of mobile robots. The underlying problem for localization is to estimate the pose from a set of 3D-2D feature correspondences, of which the main challenge is the presence of outliers, especially in changing environment. In this paper, we propose a robust solution based on efficient global optimization ...
