Searcharxiv⌕ Search

arXiv subjects

Shangsheng Wen

Publications and source records attributed to Shangsheng Wen.

9 recordsLinked to original sources
arXiv2023

Technology Report : Smartphone-Based Pedestrian Dead Reckoning Integrated with Data-Fusion-Adopted Visible Light Positioning

Pedestrian dead-reckoning (PDR) is a potential indoor localization technology that obtains location estimation with the inertial measurement unit (IMU). However, one of its most significant drawbacks is the accumulation of its measurement error. This paper proposes a visible light positioning (VLP)-integrated PDR system, which could achieve real-time and accurate indoor positioning using IMU and the camera sensor of our smartphone. A multi-frame fusion method is proposed in the encoding and decoding process of the system, reaching 98.5% decoding accuracy with a 20-bit-long ID at the height of 2.1 m, which allows the variation in the shutter speeds of cameras and heights of the LED. Meanwhile, absolute locations and step length could be calibrated with the help of a single light-emitting diode (LED), promising average accuracy within 0.5 meters in a 108-meter walk.

eess.SP↗
arXiv2022

Modern Location-based Service Technologies: Visible Light Positioning

With the development of wireless communications and the increasing computing power of variety mobile devices, LBS (Location Based Service) technologies getting more and more attention as it can provide most flexibility and convenience in modern people' s life. For this survey, we will first give a comprehensive introduction about LBS, including definition, advantages, application, and potential privacy problem. Then, we will present more detailed discussion focusing on the location technologies which is an essential part in LBS framework.

cs.NI↗
arXiv2022

A geometry method for LED mapping

With inputs from RGB-D camera, industrial camera and wheel odometer, in this letter, we propose a geometry-based detecting method, by which the 3-D modulated LED map can be acquired with the aid of visual odometry algorithm from ORB-SLAM2 system when the decoding result of LED-ID is inaccurate. Subsequently, an enhanced cost function is proposed to optimize the mapping result of LEDs. The average 3-D mapping error (8.5cm) is evaluated with a real-world experiment. This work can be viewed as a preliminary work of visible light positioning systems, offering a way to prevent the labor-intensive manual site surveys of LEDs.

eess.IV↗
arXiv2021

High Accuracy Visible Light Positioning Based on Multi-target Tracking Algorithm

In this paper, we propose a multi-target image tracking algorithm based on continuously apative mean-shift (Cam-shift) and unscented Kalman filter. We improved the single-lamp tracking algorithm proposed in our previous work to multi-target tracking, and achieved better robustness in the case of occlusion, the real-time performance to complete one positioning and relatively high accuracy by dynamically adjusting the weights of the multi-target motion states. Our previous algorithm is limited to the analysis of tracking error. In this paper, the results of the tracking algorithm are evaluated with the tracking error we defined. Then combined with the double-lamp positioning algorithm, the real position of the terminal is calculated and evaluated with the positioning error we defined. Experiments show that the defined tracking error is 0.61cm and the defined positioning error for 3-D positioning is 3.29cm with the average processing time of 91.63ms per frame. Even if nearly half of the LED area is occluded, the tracking error remains at 5.25cm. All of this shows that the proposed visible light positioning (VLP) method can track multiple targets for positioning at the same time with good robustness, real-time performance and accuracy. In addition, the definition and analysis of tracking errors and positioning errors indicates the direction for future efforts to reduce errors.

eess.SP↗
arXiv2020

High accuracy and error analysis of indoor visible light positioning algorithm based on image sensor

In recent years, with the increasing demand for indoor positioning service, visible light indoor positioning based on image sensors has been widely studied. However, many researches only put forward the relevant localization algorithm and did not make a deep discussion on the principle of the visible light localization. In this paper, we make a deep discussion on the principle of the two-light positioning algorithm and the three-light positioning algorithm based on the image sensor, which includes how these positioning algorithms work and the errors analysis. Based on the discussion above, we propose two methods to improve the positioning accuracy, which is rotation method and dispersion circle method respectively. In our experiment, we have numerically and experimentally verified the two optimization methods and we obtained good positioning results. Especially, the positioning accuracy of the dual-lamp positioning algorithm based on dispersion circle optimization is up to 1.93cm, while the average positioning error is only 0.82cm, which is state-of-the-art of the same type of positioning system at present.

eess.SP↗
arXiv2020

Indoor Localization System of ROS mobile robot based on Visible Light Communication

In this paper, an indoor robot localization system based on Robot Operating System (ROS) and visible light communication (VLC) is presented. On the basis of our previous work, we innovatively designed a VLC localization and navigation package based on Robot Operating System (ROS), which contains the LED-ID detection and recognition method, the video target tracking algorithm and the double-lamp positioning algorithm. This package exploited the principle of double-lamp positioning and the loose coupling characteristics of the ROS system, which is implemented by loosely coupled ROS nodes. Consequently, this paper combines ROS and VLC, aiming at promoting the application of VLC positioning in mature robotic systems. Moreover, it pushed forward the development of localization application based on VLC technology and lays a foundation for transplanting to other ROS robot platforms. Experimental results show that the proposed system can provide indoor localization within 1 cm and possesses a good real-time performance which takes only 0.4 seconds for one-time positioning. And if a high-performance laptop is used, the single positioning time can be reduced to 0.08 seconds. Therefore, this study confirms the practical application and the superior performance of VLC technology in ROS robot, showing the great potential of VLC localization. T he video demo of the proposed robot positioning system based on VLC can be seen in *

eess.SP↗