Resolving Loop Closure Confusion in Repetitive Environments for Visual SLAM through AI Foundation Models Assistance
Hongzhou Li,Sijie Yu,Shengkai Zhang,Guang Tan,Hongzhou Li,Sijie Yu,Shengkai Zhang,Guang Tan
In visual SLAM (VSLAM) systems, loop closure plays a crucial role in reducing accumulated errors. However, VSLAM systems relying on low-level visual features often suffer from the problem of perceptual confusion in repetitive environments, where scenes in different locations are incorrectly identified as the same. Existing work has attempted to introduce object-level features or artificial landmar...
