Demonstration of A Visible Light Receiver Using Rolling-Shutter Smartphone Camera

Tran, Tuan-Kiet; Huynh, Huu-Thuan; Nguyen, Dong; Le, Dinh-Dung; Tran, Thi-Hong; Nakashima, Yasuhiko

doi:10.1109/atc.2018.8587521

Cited by 6 publications

(1 citation statement)

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“…A survey of recent literature on VLP-based indoor robot navigation yields only a handful of papers. These works utilize a rolling shutter effect (RSE) camera as the light sensing device (please see [20][21][22] for examples of RSE-based VLP systems). Though the method uses more computer computation time and a complex algorithm because of the involvement of image processing and classification algorithm, the availability of ubiquitous CMOS image sensor cameras in most smartphones has made them the preferred choice among researchers.…”

Section: Related Workmentioning

confidence: 99%

Visible Light Positioning-Based Robot Localization and Navigation

Chew,

Alam,

Noble

et al. 2024

Electronics

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Visible light positioning or VLP has been identified as a promising technique for accurate indoor localization utilizing pre-existing lighting infrastructure. Robot navigation is one of the many potential applications of VLP. Recent literature shows a small number of works on robots being controlled by fusing location information acquired via VLP that uses a rolling shutter effect camera as a receiver with other sensor data. This paper, in contrast, reports on the experimental performance of a cartesian robot that was controlled solely by a VLP system using a cheap photodiode-based receiver rigidly attached to the robot’s end-effector. The receiver’s position was computed using an inverse-Lambertian function for ranging followed by multi-lateration. We developed two novel methods to leverage the VLP as an online navigation system to control the robot. The position acquired from the VLP was used by the algorithms to determine the direction the robot needed to move. The developed algorithms guided the end-effector to move from a starting point to target/destination point(s) in a discrete manner, determined by a pre-determined step size. Our experiments consisted of the robot autonomously repeating straight line-, square- and butterfly-shaped paths multiple times. The results show median errors of 27.16 mm and 26.05 mm and 90 percentile errors of 37.04 mm and 47.48 mm, respectively, for the two methods.

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Section: Related Workmentioning

confidence: 99%