RF-MVO: Simultaneous 3D object localization and camera trajectory recovery using RFID Devices and a 2D monocular camera

Publication Type:
Conference Proceeding
Proceedings - International Conference on Distributed Computing Systems, 2018, 2018-July pp. 534 - 544
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© 2018 IEEE. Most of the existing RFID-based localization systems cannot well locate RFID-tagged objects in a 3D space. Limited robot-based RFID solutions require reader antennas to be carried by a robot moving along an already-known trajectory at a constant speed. As the first attempt, this paper presents RF-MVO, which fuses battery-free RFID and monocular visual odometry to locate stationary RFID tags in a 3D space and recover an unknown trajectory of reader antennas binding with a 2D monocular camera. The proposed hybrid system exhibits three unique features. Firstly, since the trajectory of a 2D monocular camera can only be recovered up to an unknown scale factor, RF-MVO combines the relative-scale camera trajectory with depth-enabled RF phase to estimate an absolute scale factor and spatially incident angles of an RFID tag. Secondly, we propose a joint optimization algorithm consisting of coarse-to-fine angular refinement, 3D tag localization and parameter nonlinear optimization, to improve real-time performance. Thirdly, RF-MVO can determine the effect of relative tag-antenna geometry on the estimation precision, providing optimal tag positions and absolute scale factors. Our experiments show that RF-MVO can achieve 6.23cm tag localization accuracy in a 3D space and 0.0158 absolute scale factor estimation accuracy for camera trajectory recovery.
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