Internet of Things Collaborative Localization
Internet of Things Collaborative Localization: Traditional non-collaborative localization systems (such as GPS, BeiDou, etc.) rely on ranging between the node to be located and several anchor points for positioning. In IoT application scenarios, these systems suffer from issues such as low reliability, difficult deployment, and low positioning accuracy. Our research group explores the use of collaborative localization technology to address the pain points of these classical localization techniques. Nodes to be located use technologies such as vision and wireless to obtain ranging observation data. Subsequently, computer vision collaborative SLAM, Bayesian message passing, optimization theory, and other methods are employed to fuse multi-source data for node collaborative localization. Additionally, sensors such as the UWB DW3000 chip, monocular/binocular/RGB-D cameras are used to acquire ranging data, and embedded computing platforms are utilized for data transmission, storage, and processing, thereby realizing the hardware implementation of collaborative localization.
