Abstract
In this paper, a novel three-dimensional (3D) indoor visible light positioning (VLP) algorithm using the Cayley–Menger determinant (CMD) with a cost function is proposed and experimentally tested to track a drone for industrial applications. The proposed algorithm uses optical received signal strength (RSS) for estimating the drone’s 3D position without prior knowledge of its height. This reduces the need for additional height sensors used in some 3D VLP systems. The performance of the proposed algorithm in terms of positioning error is also compared with a linear least squares (LLS) trilateration algorithm, with and without tilting of the receiver and with multipath reflections. The simulation results show that the proposed algorithm is more accurate and outperforms the LLS algorithm by a median improvement of 21% and is also more robust to the effect of tilting, as well as in the presence of multipath reflections. Furthermore, the proposed algorithm has been experimentally tested and compared with the LLS algorithm in a VLP test bed measuring 4 × 4 × 4.1 m 3 . The experimental results show that the median errors for LLS are 11.4 cm, while the median errors for CMD are 10.5 cm, which results in an error decrease of 8% when CMD with a cost function is used.
Highlights
Unmanned aerial vehicles (UAVs), commonly known as drones, are used for different applications, such as to perform visual inspections of a variety of indoor and outdoor environments, as they offer a safe and cost-effective way to inspect different heights and areas that are hard to reach
The performance of the proposed Cayley–Menger determinant (CMD) algorithm was evaluated in terms of positioning error for a typical industrial deployment, adhering to the standardized illumination levels, by considering (i) normal line-of-sight and untilted reception, (ii) different tilt angles of the receiver and (iii) multipath reflections
The performance of the algorithm was first evaluated to investigate the effect of tilt on the height estimation using the received signal strength (RSS) and cost function for a position when the receiver was at (10 m, 6 m, 2 m)
Summary
Unmanned aerial vehicles (UAVs), commonly known as drones, are used for different applications, such as to perform visual inspections of a variety of indoor and outdoor environments, as they offer a safe and cost-effective way to inspect different heights and areas that are hard to reach. This eliminates the need for manual inspections [1]. The distances for different heights between the LEDs and the drone are obtained with a CMD positioning algorithm using the RSS.
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