Enabling High-Precision Visible Light Localization in Today's Buildings.

For over one decade, research in visible light positioning has focused on using modulated LEDs as location landmarks. But the need for specialized LED fixtures, and the associated retrofitting cost, has been hindering the adoption of VLP. In this paper, we forgo this approach and design iLAMP to enable reliable, high-precision VLP using conventional LEDs and fluorescent lamps inside today's buildings. Our key observation is that these lamps intrinsically possess hidden visual features, which are imperceptible to human eyes, but can be extracted by capturing and processing the lamps' images using a computational imaging framework. Simply using commodity smartphones' front cameras, our approach can identify lamps within a building with close to 100% accuracy. Furthermore, we develop a geometrical model which combines the camera image with gyroscope/accelerometer output, to estimate a smartphone's 3D location and heading direction relative to each lamp landmark. Our field tests demonstrate a mean localization (heading) precision of 3 cm (2.6 degree) and 90-percentile 3.5 cm (2.8 degree), even if a single lamp falls in the camera's field of view.