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Proceedings Paper

An indoor co-positioning algorithm using WLAN and monocular vision
Author(s): Xiaoqiang Jiang; Hu Lu; Huan Min
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Paper 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

Paper Details

Date Published: 31 January 2020
PDF: 11 pages
Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 1142704 (31 January 2020); doi: 10.1117/12.2548433
Show Author Affiliations
Xiaoqiang Jiang, Air Force Engineering Univ. (China)
Hu Lu, Air Force Engineering Univ. (China)
Huan Min, Air Force Engineering Univ. (China)


Published in SPIE Proceedings Vol. 11427:
Second Target Recognition and Artificial Intelligence Summit Forum
Tianran Wang; Tianyou Chai; Huitao Fan; Qifeng Yu, Editor(s)

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