Abstract
The vision SLAM technology is the key technology of robot navigation and unmanned driving. In order to further study the accuracy of multi-view SLAM positioning and mapping applications, this paper combines omnidirectional imaging and SLAM technology, improves the existing technical model in the field of omnidirectional imaging, studies the pose map optimization and SLAM overall adjustment technology based on object constraints and global consistency, and carries out omnidirectional SLAM point cloud reconstruction and 3D mapping. Through the time synchronization experiment of Ladybug 5 Plus and Femtomes Mini2-D-INS, the two positioning results of the system and the GNSS measurement results are compared and analysed.
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