Benefiting
from the development of image sensors and the popularity of light-emitting
diode (LED) lighting technology, visible light positioning (VLP) technology
based on image sensors has ushered in vigorous development and broad prospects,
which can provide low-cost and high-accuracy position service. However, the
existing approaches require dense LEDs or sensors such as gyroscopes to assist
positioning, which limit the area and lower the accuracy of positioning because
of the errors from imperfect sensors. In this paper, we propose a simultaneous
localization and calibration VLP method based on double coplanar circular LED
lights aiming to get rid of the dependence on additional sensors and dense LED
transmitters. By the pinhole camera model and the perspective projection of
circle, our proposed method extends the available position area and relaxes the
required quantity of LED to two. The experiment result shows that our system
has a mean 3D positioning accuracy of 7.91cm, a mean angle error of less than
1.6°, and an average latency of 182ms on mobile devices.
Benefiting from the development of image sensors and the popularity of light-emitting diode (LED) lighting technology, visible light positioning (VLP) technology based on image sensors has ushered in vigorous development and broad prospects, which can provide low-cost and high-accuracy position service. However, the existing approaches require dense LEDs or sensors such as gyroscopes to assist positioning, which limit the area and lower the accuracy of positioning because of the errors from imperfect sensors. In this paper, we propose a simultaneous localization and calibration VLP method based on double coplanar circular LED lights aiming to get rid of the dependence on additional sensors and dense LED transmitters. By the pinhole camera model and the perspective projection of circle, our proposed method extends the available position area and relaxes the required quantity of LED to two. The experiment result shows that our system has a mean 3D positioning accuracy of 7.91cm, a mean angle error of less than 1.6°, and an average latency of 182ms on mobile devices.
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