An indoor co-positioning algorithm using WLAN and monocular vision

Xiaoqiang Jiang; Hu Lu; Huan Min

doi:10.1117/12.2548433

31 January 2020 An indoor co-positioning algorithm using WLAN and monocular vision

Xiaoqiang Jiang, Hu Lu, Huan Min

Proceedings Volume 11427, Second Target Recognition and Artificial Intelligence Summit Forum; 1142704 (2020) https://doi.org/10.1117/12.2548433
Event: Second Target Recognition and Artificial Intelligence Summit Forum, 2019, Changchun, China

Abstract

Simultaneous localization and mapping (SLAM) had been developed in the robotics community initially, and gradually applied to indoor positioning. The monocular visual SLAM lacks metric distances information due to scale ambiguity, so cannot be used in many application scenarios. This paper proposed a precision co-positioning and mapping algorithm based on WLAN and mono vision. This method can estimate the scale factor of monocular VSLAM and get the position in real scale space. Furthermore, the WLAN localization and monocular vision is fused by factor graph model to realize accurate positioning and sparse mapping. Experiment results show that the algorithm can estimate scale factor well and reached positioning accuracy of decimeter, which has good theoretical research and practical value in the field of mobile robot navigation in indoor and outdoor environment

Citation Download Citation

Xiaoqiang Jiang, Hu Lu, and Huan Min "An indoor co-positioning algorithm using WLAN and monocular vision", Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 1142704 (31 January 2020); https://doi.org/10.1117/12.2548433

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