A High-Precision Positioning Scheme Under Non-Point Visible Transmitters

Visible Light Positioning (VLP) is widely recognized as a cost-effective solution for indoor positioning with increasing demand. However, the nonlinearity and highly complex relationship between three-dimensional world coordinate and two-dimensional image coordinate hinders the good performance of image-sensor-based VLP. Therefore, there is a need to develop effective VLP algorithms to locate the positioning terminal using image sensor. Besides, due to the high computational cost of image processing, most existing VLP systems do not achieve satisfactory performance in terms of real-time ability and positioning accuracy, both of which are significant for the performance of indoor positioning system. In addition, the accurate identification of the ID information of each LED (LED-ID) is important for positioning, because if the LED-ID is not recognized well, the positioning can only be achieved in a particular positioning unit and cannot be applied to a large scene with many LEDs. Therefore, an effective image-sensor-based double-light positioning system is proposed in this paper to solve the above problems. We also set up relevant experiments to test the performance of the proposed system, which utilizes the rolling shutter mechanism of the Complementary Metal Oxide Semiconductor (CMOS) image sensor. Machine learning was used to identify the LED-ID for better results. Simulation results show that the proposed double-light positioning system could deliver satisfactory performance in terms of both the real-time ability and the accuracy of positioning. Moreover, the proposed double-light positioning algorithm has low complexity and takes the symmetry problem of angle into consideration, which has never been considered before. Experiments confirmed that the proposed double-light positioning system can provide an accuracy of 3.85 cm with an average computing time of 56.28 ms, making it a promising candidate for future indoor positioning applications.

In this paper, we propose a novel visible light positioning (VLP) scheme under multi-path propagation, which is a practical scenario that has not been well studied for VLP. The new scheme exploits the so-called dual-mode light-emitting diode (DM-LED) of different radiation lobe mode numbers at the transmitter and a photodiode at the receiver. Specifically, we devise a method that utilizes a radiation angle measurement approach for DM-LED, derive the Cramér-Rao lower bound (CRLB) of the estimated distance and analyze the characteristics of key parameters. In addition, two localization algorithms based on linear and nonlinear least squares methods are developed. Simulation results show that under the ideal light-of-sight scenario, the CRLB of the proposed VLP scheme can be close to that of the conventional received signal strength (RSS) aided VLP scheme. Furthermore, we implement the first ever prototype DM-LED lamp to validate the new DM-LED aided VLP system model. Both simulation and experiment results demonstrate that the proposed system outperforms its RSS-aided VLP counterpart in terms of positioning accuracy in the more realistic, and thus more challenging multi-path scenario, even with a tilting receiver.

Visible light positioning (VLP) is widely believed to be a cost-effective answer to the growing demand for service-based indoor positioning. Meanwhile, high accuracy localization is very important for mobile robots in various scenes including industrial, domestic and public transportation workspace. In this paper, an indoor robot VLP localization system based on Robot Operating System (ROS) is presented for the first time, aiming at promoting the application of VLP in mature robotic system. On the basis of our previous researches, we innovatively designed a VLP localization package which contains the basic operation control of the robots, the features extraction and recognition of the LED-ID, cm-level positioning, and robust dynamic tracking algorithms. This package exploited the proposed lightweight algorithm, distributed framework design, the loose coupling characteristics of the ROS, and the message communication methods among different nodes. What's more, an efficient LED-ID detection scheme is proposed to ensure the lightweight and accuracy of the positioning. A prototype system has been implemented on a Turtlebot3 Robot <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">11</sup> Experiment Demonstration is available at: https://kwanwaipang.github.io/Image/ROS.mp4.. Experimental results show that the proposed system can provide robot indoor positioning accuracy within 1 cm and an average computational time of only 0.08 s.

This paper tackles indoor receiver localization as a regression task using visible light positioning (VLP). This technology has gained prominence as an alternative to conventional indoor positioning. Traditional systems such as WiFi and ZigBee face notable drawbacks: electromagnetic interference, added infrastructure, limited accuracy, and high deployment costs. In general, classical positioning approaches—lateration, triangulation, proximity, and least squares—typically infer location from measurements like received signal strength (RSS), time of arrival (TOA), time difference of arrival (TDOA), or angle of arrival (AOA). However, in real-world VLP scenarios, these methods face difficulties since they depend on ideal signals, which means unaffected by physical obstacles and perfectly aligned between transmitters and receiver. Our work proposes the application of the extreme learning machine (ELM) algorithm, its regularized version (R-ELM) and the Levenberg-Marquardt algorithm (LMA), to predict the receiver’s position based simply on the light signals emitted by light-emitting diodes (LEDs) and captured by a photodiode (PD). To evaluate the overall performance of these models, two experimental datasets were used: one in a 2D environment with 7344 RSS samples and another novel in a 3D environment with 27000 training records and 18000 testing samples by analyzing power spectral densities. To assess performance and analyze parameter optimization of ELM, R-ELM, and LMA, metrics such as root mean square error (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RMSE</i>), correlation coefficient (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i>), training and testing times were used. By considering the state of the art, the LMA model proved to be the most accurate in the 2D environment (RMSE less than 10 cm), although its training time was excessive (over one hour), incompatible with for real-time applications (time variant channels). In contrast, the R-ELM achieved an accuracy of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RMSE</i> = 12.4806 cm and completed its training in 31.2 ms (real-time learning), positioning it as a much more efficient alternative compared to LMA. For the 3D dataset, the R-ELM also showed the best overall performance, with an average RMSE close to 22.4784 cm and a training time of 1.0250 s. Incorporating both the dominant frequency and power as inputs into the ELM enhanced the model’s accuracy compared to using each input separately. Lastly, RMSE was evaluated as a function of the distance from the center of the room of each data set, concluding that the R-ELM is more stable in areas with weak signals or missing data, which is particularly valuable in real environments where the signal is not always homogeneous. Finally, the results demonstrate that it is possible to achieve a precise and fast positioning system based on VLP using the R-ELM, as this model generally achieves higher accuracy and computational efficiency.

Visible light positioning (VLP) has been widely studied since it can provide high accuracy indoor positioning functionality with light-emitting diode (LED) beacons. However, existing VLP systems still suffer from high positioning latency and low robustness in practical scenarios. A robust and low-complexity image processing algorithm is proposed for LED region-of-interest (ROI) extraction and tracking, which contributes to handle various harsh situations and support accurate VLP with low positioning latency. Experimental results show that the proposed LED-ROI scheme can achieve an average tracking accuracy of 0.46 cm and better real-time performance and robustness compare with the others current LED-ROI methods.

Visible light positioning (VLP) has been studied widely due to its high accuracy and low cost in the field of location-based services (LBS). However, many existing VLP systems have the requirements that the receiver should be placed horizontally and more than three LED lamps should be used, which are difficult to meet in practical scenarios. Therefore, it is necessary to develop a novel VLP algorithm for tilted conditions. An effective and simple VLP system while the receiver is tilted based on double-LED lamps is proposed in this paper. The vertical position can be determined by combining the information from angle sensors with geometric information. Through analyzing the imaging characteristics of the tilted state, we can utilize the relationship of similarity to calculate the location of the mobile receiver. Experimental results show that the positioning accuracy of our proposed algorithm can reach 5.48 cm.

In this paper, a positioning algorithm based on the combination of K-means clustering and deep neural networks (DNNs) is first presented for multiple light emitting diodes (LEDs) integrated with visible light positioning (VLP) systems. We extracted the maximum value from the collected optical power of LEDs, utilizing the ratio of each optical power to this maximum optical power as the input training data. The experimental results demonstrate that the proposed algorithm outperformed the conventional DNN algorithm in terms of anti-jamming capability and positioning accuracy. In addition, the positioning accuracy of the proposed system reached a millimeter level, which is the highest experimental VLP accuracy, to the best of our knowledge.

Visible light positioning (VLP) has become a promising indoor localization approach as it can provide sub-meter localization. VLP usually requires no less than three LED lamps for angle-of-arrival (AoA) or received-signal-strength (RSS) based localization. However, it is hard to identify multiple LED lamps in some indoor environments, such as a long corridor or tunnel, which makes existing VLP useless. To address this problem, we propose a VLP approach using only a single LED lamp. In this approach, we utilize the inertial measurements to infer rotation angles and exploit visual projection geometry to calibrate rotation angles. The experiment results demonstrate the proposed VLP approach can achieve sub-meter positioning accuracy by using only one LED lamp.

Indoor positioning systems based on visible light communication (VLC) using white light-emitting diodes (WLEDs) have been widely studied in the literature. In this paper, we present an indoor visible-light positioning (VLP) system based on red–green–blue (RGB) LEDs and a frequency division multiplexing (FDM) scheme. This system combines the functions of an FDM scheme at the transmitters (RGB LEDs) and a received signal strength (RSS) technique to estimate the receiver position. The contribution of this work is two-fold. First, a new VLP system with RGB LEDs is proposed for a multi-cell network. Here, the RGB LEDs allow the exploitation of the chromatic space to transmit the VLP information. In addition, the VLC receiver leverages the responsivity of a single photodiode for estimating the FDM signals in RGB lighting channels. A second contribution is the derivation of an expression to calculate the optical power received by the photodiode for each incident RGB light. To this end, we consider a VLC channel model that includes both line-of-sight (LOS) and non-line-of-sight (NLOS) components. The fast Fourier transform (FFT) estimates the powers and frequencies of the received FDM signal. The receiver uses these optical signal powers in the RSS-based localization application to calculate the Euclidean distances and the frequencies for the RGB LED position. Subsequently, the receiver’s location is estimated using the Euclidean distances and RGB LED positions via a trilateration algorithm. Finally, Monte Carlo simulations are performed to evaluate the error performance of the proposed VLP system in a multi-cell scenario. The results show a high positioning accuracy performance for different color points. The average positioning error for all chromatic points was less than 2.2 cm. These results suggest that the analyzed VLP system could be used in application scenarios where white light balance or luminaire color planning are also the goals.

This paper assesses the accuracy of a three-dimensional Visible Light Positioning (VLP) algorithm for two different Light Emitting Diode (LED) configurations using the same four LEDs, but mounted at different locations on the ceiling. The two configurations are both simulated and measured at 22801 test points. It is observed that a classic square LED configuration results in position ambiguities, causing errors up to several meters. Alternatively, a star-shaped LED configuration is able to uniquely reconstruct the photodiode's location. For LEDs at a height of approximately 3 m above the receiver, median errors of 12.7 cm and maximal errors of 21.1 cm are experimentally obtained, showcasing the applicability of 3D VLP for drone navigation.

Visible light positioning (VLP) has developed rapidly with the ubiquitous lighting infrastructure in recent years. Based on classic trilateration or triangulation, VLP usually requires at least three light sources which makes it infeasible in some scenarios where sparse LED luminaries are mounted. In this paper, we focus on VLP in such scenarios and propose a VLP method based on a single LED luminaire as the light transmitter and commercial off-the-shelf smartphone as the receiver. A critical problem that needs to be addressed is to derive the accurate orientation of the smartphone. Although the inertial measurement unit of the smartphone can be used to obtain the orientation, the measurement error severely degrades the positioning accuracy. To address the measurement error, this paper innovates in exploiting projective geometry to calibrate the orientation measurements. We build an experimental platform to evaluate the proposed VLP method. The experimental results show that the proposed VLP method can achieve a submeter accuracy and the indoor positioning errors are within 0.16 m by 90%.

Visible light positioning (VLP) is an emerging positioning technique that utilizes indoor light sources to broadcast archer locations through visible light communication (VLC). Benefited by the densely deployed light lamps, VLP holds the promise for more accurate positioning accuracy than RF based approaches, and thus enables interesting applications such as retail navigation and shelf-level advertising in supermarkets and shopping malls. However, we observe that in existing VLP systems, receiving devices are heavily burdened in handling light flickering for VLC. In order to prevent human from being disturbed, the VLC transmitter lamps have to transmit pulses in a high rate (over 1kHz). Since the pulse rate far exceeds the cameras' sampling capability (30fps), receiver design either requires customized light sensor with cumbersome calibration on receiving signal strength [2] or processing high resolution images to leverage rolling shutter effect of the CMOS camera to decode message [1]. The heavy burden on receiving devices motivated us to try getting rid of light flickers. Since human eyes normally can not perceive changes in polarization, the idea is to modulate polarization instead of intensity for communication. In this demo, we demonstrate the VLC system in our VLP design [3] which realizes this idea. It enables lightweight VLC that is even affordable in wearables (Google Glass), without incurring hardware modification or computation off-loading. Moreover, it also makes other types of illuminating light beyond LED light (even sun light) possible to construct communication, therefore eliminates the barrier for deploying future VLC-based applications. As detailed in the full paper [3], our design was inspired by the liquid crystal display (LCD), from which we borrowed polarizer and liquid crystal. Liquid crystal has the property to change the polarization of bypassing polarized light according to the applied voltage. We use polarizer to polarize illuminating light and leverage liquid crystal to modulate bits through changing the light's polarization. The receiver can thus detect changes in polarization with a polarizing film, through which different polarizations result in different intensities. Since the SNR of such communication channel may significantly vary with the mobility of receiving device, we propose to add a dispersion filter to the transmitter. The dispersion filter can cast different frequency of lights into different polarization directions so that SNR in different receiving directions are evened. With the above techniques, VLC transmitter generates signal in low baud rate and mobile devices can perform VLC through camera directly. The communication is long in distance and lightweight enough for resource-constrained devices since the information is carried in intensity changes rather than certain image patterns in rolling shutter approaches. In this demo, we will illustrate the prototype implementation of the VLC communication system. We use incandescent lamps as illuminating light sources. The transmitter consists of a polarizing film, a liquid crystal layer, a dispersor and a control board. The receiver is demonstrated in Android smartphone with polarizing film in front of the camera.

Visible light positioning (VLP) is an accurate indoor positioning technology that uses luminaires as transmitters. In particular, circular luminaires are a common source type for VLP, which are typically treated only as point sources for positioning, while ignoring their geometry characteristics. In this paper, the arc feature of the circular luminaire and the coordinate information obtained via visible light communication (VLC) are jointly used for positioning, and a novel perspective arcs approach is proposed for VLC-enabled indoor positioning. The proposed approach does not rely on any inertial measurement unit and has no tilted angle limitation at the user. First, a VLC assisted perspective circle and arc algorithm (V-PCA) is proposed for a scenario in which a complete luminaire and an incomplete one can be captured by the user. Based on plane and solid geometry theory, the relationship between the luminaire and the user is exploited to estimate the orientation and the coordinate of the luminaire in the camera coordinate system. Then, the pose and location of the user in the world coordinate system are obtained by single-view geometry theory. Considering the cases in which parts of VLC links are blocked, an anti-occlusion VLC assisted perspective arcs algorithm (OA-V-PA) is proposed. In OA-V-PA, an approximation method is developed to estimate the projection of the luminaire’s center on the image and, then, to calculate the pose and location of the user. Simulation results show that the proposed indoor positioning algorithm can achieve a 90th percentile positioning accuracy of around 10 cm. Moreover, an experimental prototype is implemented to verify the feasibility. In the established prototype, a fused image processing method is proposed to simultaneously obtain the VLC information and the geometric information. Experimental results in the established prototype show that the average positioning accuracy is less than 5 cm for different tilted angles of the user.

As an application of visible light communication (VLC), visible light positioning (VLP) technology has great potential for vehicle positioning due to its characteristics of no electromagnetic interference, low cost, and high positioning accuracy. In addition, the light emitting diode (LED) in street lights, traffic lights and vehicle lighting systems makes this positioning solution attractive for vehicular applications. However, the modulated LED signal will bring blooming effects on the images captured by a complementary metal oxide semiconductor (CMOS) camera. And it will decrease the positioning performance. Meanwhile, positioning errors will happen when the CMOS camera is tilted. In the paper, a vehicle positioning scheme based on VLC is proposed and experimentally demonstrated. It uses LED street light as a transmitter and the CMOS camera as a receiver. To mitigate the blooming effect in the CMOS camera based VLC, a bit length estimation (BLE) based sampling scheme is proposed to obtain the reference location information from the captured images. In addition, a novel angle compensation scheme combined with a particle filter is proposed to improve the accuracy of vehicle positioning when the CMOS camera is tilted. The experiments are performed under moving speeds of 40 to 80 cm/s and the measured distances of 80 to 115 cm. Assuming the performance of the proposed demonstrator is not modified when upscaling its size to a real scenario (such as speeds of 4 to 8 m/s and distances between the LED and camera of several meters), it can be concluded that as the speed of the moving vehicle is 8 m/s, the proposed vehicle positioning scheme based on VLC can achieve positioning accuracy of 0.128 m and 0.13 m for the tilt angles of 9° and 15.5°, respectively.

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